Barriers and Enablers to Advanced Technology Adoption for UK Businesses

Question 1

1.  Executive Summary

Accepted Answer

1.1 Background

The UK has witnessed poor labour and total factor productivity (TFP) growth since the 2008 financial crisis. There is now significant interest in increasing the adoption of ‘advanced technologies’, like Artificial Intelligence (AI), due to their potential for driving higher productivity growth.

A deeper, more nuanced understanding is needed to explore how and why barriers and enablers prevent or facilitate technology adoption across the UK business population. Qualitative work is needed to explore in particular how businesses weigh up and negotiate these as well as the relationships and inter-connectedness between these factors. Insights from this work will contribute to the DCMS/DSIT evidence base on drivers of advanced technology adoption in businesses.

1.2 Research design

The aims of this qualitative research are to further our understanding of:

The drivers of business decisions around adoption of advanced technologies and
How businesses are experiencing barriers and enablers to adoption in more depth, including how these differ according to business characteristics.
What government interventions businesses need and want to address barriers.

There is no universally accepted definition of ‘advanced technology’ but this project has used the following working definition:

‘cutting-edge technologies at the boundaries of existing scientific, engineering and technological knowledge which are likely to integrate elements from domains such as digital technology, data science and analytics, AI, robotics and material science.’^{[footnote 1]}

The research has focused on adoption of advanced technologies in 4 technology clusters^{[footnote 2]} derived from DSIT’s Innovation Diffusion and Adoption (IDA) Survey:

Cluster 1: Information and communication technologies;
Cluster 2: Advanced computing technologies;
Cluster 3: Advanced Manufacturing and Materials; and
Cluster 4: Energy and Environmental Technologies

This research focuses on the adoption decision rather than experiences of integration , and drivers of adoption decisions instead of what businesses are doing to drive growth.

The research was conducted in iterative phases of qualitative inquiry. The scoping phase included a literature review of 40 documents and a stakeholder workshop. The primary research involved 80 online, semi-structured one-hour qualitative interviews with businesses across the UK in Manufacturing, Retail, Finance, Creative industries, and Professional, scientific and technical activities (referred to as Professional services throughout this report). In addition, 8 stakeholder interviews with sector and technology experts were conducted to enhance the dataset.

1.3 Catalysts and constraints: key factors driving business adoption decision-making

This research finds that business decision-making on advanced technology adoption is complex and that decisions are shaped by the dynamic interplay of multiple interrelated factors. There was no single most influential determinant of adoption decisions. Instead, businesses reported experiencing multiple catalysts and constraints which act with varying degrees of strength as push and pull forces on their adoption decision-making and businesses experiences of these forces varied significantly across the sample. Overall, business risk profile, clarity of use case, affordability, and regulation were widely reported to exert strong influence on adoption decision-making.

The catalysts and constraints identified tended to be opposing sides of a set of key factors. Taking a Systems Approach, the research identified 19 factors, listed below. Aligned with the Technology-Organisation-Environment (TOE^{[footnote 3]} Framework, which the literature review for this study concluded was an appropriate paradigm for the fieldwork, these factors emerged across 3 levels: technology, organisation, and the external environment context. These 3 levels are nested and the outer levels influence the internal ones, but all 3 levels and all 19 factors collectively influence the adoption decision. The factors inter-relate, within and across the 3 levels.

Technology level: clarity and relevance of use case, technology risks, perceptions of usability, and systems alignment.
Organisational level: affordability, access to skills, leadership attitudes, business risk profile, strategic ambition, presence of supportive structures, alignment with brand values, employee attitudes
External level: standards and regulation, shareholder/ investor pressure, competitor dynamics, customer dynamics, supply chain dynamics, sector norms, access to trusted advice.

As well as exploring the system, we also need to consider the decision-making dynamics that occur within businesses, where adoption decisions are ultimately made. To understand why advanced technologies are adopted or not, we must recognise that the relevance and impact of the factors shift at different points in a business’s decision-making process. This report applies the Willingness, Capability, and Capacity model, summarised below, to explore how the factors identified exert pressure on business decision-making^{[footnote 4]}.

Category 1: Willingness to consider a technology.

This encompasses appetite and openness to considering a technological solution, which is shaped by attitudes and expectations related to potential benefits (and costs) to the business.

Category 2: Capability to implement change.

This refers to the degree to which willing businesses are able to adopt innovations with the resources that they currently have or are able to access (either by acquiring new resources or using external ones).

Category 3: Capacity to devote resources.

This is the ease with which willing business with the requisite capabilities can direct and devote resources to technology adoption at a particular moment in time.

The 19 factors identified could all act as either a catalyst or constraint on adoption decision-making. The factors were also highly inter-related. In various combinations, these factors influenced business willingness, capability, and capacity to adopt. Overall, this report finds that, while the strength and importance of the factors were seen to vary across the sample, all of the factors were seen to influence adoption decisions in different ways. In addition, business willingness, capability and capacity to adopt also varied across the sample and were influenced by the 19 factors identified – but more of the factors identified aligned with willingness than capability or capacity.

1.4 Applying lenses: understanding variation in business experiences of catalysts and constraints across the sample

The importance of each of the 19 factors was not uniform across the sample. Different functions and contexts for each of the 5 technology clusters meant that different catalysts and constraints played more prominent roles for each of them.

For Information and communication technologies (cluster 1), efficiency-based use cases and competitor pressure played a key role but there were widespread concerns about functionality.
For Advanced computing technologies (cluster 2), efficiency and productivity-focused use cases and costs were key factors for consideration, as well as systems alignment.
For Advanced manufacturing and materials (cluster 3), alignment with business strategy was key along with use case and cost.
For Energy and environmental technologies (cluster 4), the ability to demonstrate their commitment to sustainability was key and this meant a range of factors played a role (e.g. client and supply chain dynamics, strategy and brand values, and regulation).

Businesses experienced the catalysts and constraints differently and some factors played a more prominent role than others across the 5 sectors included in this research. These were selected to provide breadth to the research. For each sector, there was a complex interplay between the factors although market pressure cut across industries.

In Manufacturing, use cases focused on efficiencies and cost reduction, costs and system alignment were key, and regulatory requirements and market pressures played an important role.
In Retail, use cases focused on efficiency and improved customer experience were key, and cost and customer dynamics also played an important role.
In Finance, use cases focused on efficiency, speed and precision were key, and regulations, competitor pressures and sector norms also played an important role.
In Professional services, cluster one technologies were most appealing and customer and competitor pressures played a key role as well as regulation and system alignment.
In Creative industries, market pressure played a key role, as well as customer dynamics and concerns about regulation and employee attitudes.

Whilst there was meaningful variation in experiences across the sectors, other more nuanced patterns of business experiences emerged. This report introduces a typology to help enhance understanding of the variation in business experiences. The typology focuses on explaining likelihood to adopt advanced technologies and the 2 strongest drivers of this variation were:

The level of internal buy-in to the value of advanced technologies to their strategy in the business, and
The business risk profile.

6 types were identified as: pioneers, strategic adopters, pragmatic followers, reluctant adopters, tech resistors, and detached traditionalists. It is important to understand that some factors were more prominent for each of the business types and that therefore different types of interventions and support are likely to be more and less effective for each.

1.5 Conclusions about effective policy interventions to drive business uptake of advanced technologies

This research finds that businesses make adoption decisions within a complex system of interrelated factors, weighing pressures from multiple sources. Understanding this system and how the factors inter-relate is important, as intervention in one area can create ripple effects that influence business decision-making dynamics.

The factors shape business willingness, capability and capacity to adopt new technologies. Understanding which are seen to be the most important drivers and how they affect business willingness, capacity and capability can help determine the most effective mix of government interventions to encourage advanced technology uptake. We note that this research finds that intervention is needed to influence all 3 categories across the UK business population.

Businesses identified 4 key types of intervention as likely to be the most effective in encouraging them to adopt advanced technology:

Market interventions (namely changing regulations and standards);
Government supported staff training for businesses;
Provision of information to raise awareness of the benefits of advanced technologies; and
Financial incentives.

As suggested above, businesses saw government interventions as most beneficial when used in combination. The interventions that appealed to businesses mapped onto the Willingness, Capability, and Capacity (WCC) model as illustrated in Table 1 below.

Table 1: Summary of interventions to support adoption across the Willingness, Capability, and Capacity model

Aspect of WCC	Suggested interventions
1. Willingness to consider a technology	Providing information to increase awareness of advanced technologies and their benefits; Helping businesses realise use cases; Promotion of knowledge sharing and best-practice; Market interventions to provide regulatory clarity
2. Capability to implement change	Financial incentives to address cost constraints; Staff training programmes to encourage adoption readiness; Support to improve business capabilities; Information or guidance to enable more confident decisions for those with high uncertainty/limited time; Harmonise and streamline regulation to remove specific barriers
3. Capacity to devote resources	Financial incentives to enable re-orientation towards advanced technology driving growth; Address resource-limiting aspects of environment and market; Tailored information to highlight capacity/growth building potential of technology

In addition, this research identified 6 business segments with varied contexts, perspectives and needs. These segments could benefit from a targeted, distinguishing approach to tech adoption. The report outlines which interventions and types of support are most likely to be effective at increasing willingness, capability and capacity for each of business type:

Pioneers had the fewest barriers to adoption but uptake could be increased through tailored financial incentives and highly tailored information from verified suppliers and experts.
Strategic adopters were also likely to be adopting, but this could be further supported by government action to increase skills in the market, training, and peer support initiatives.
Pragmatic followers tended to take a relatively passive approach and therefore interventions focused on increasing visibility of opportunities and tailored bespoke support to overcome barriers would be most effective.
Reluctant adopters would benefit from interventions designed to increase their willingness and help them overcome risk aversion, such as increasing visibility of relevant use cases, increasing credibility of options, and supporting them to overcome concerns about regulation and knowledge gaps.
Technology resistors were unlikely to consider advanced technologies as a solution and therefore tax incentives and regulatory requirements are likely to be most effective.
Detached traditionalists did not see advanced technologies as for them and therefore need interventions to help them see the value and relevance of these technologies to their business (e.g. awareness raising and trust building initiatives).

Overall, this report aims to provide useful insight to a range of stakeholders across government working on increasing uptake of advanced technologies by UK businesses.

Question 2

2.  Research Design

Accepted Answer

2.1 Background

The UK has witnessed poor labour and total factor productivity (TFP) growth since the 2008 financial crisis. There is now significant interest in increasing the adoption of advanced technologies, like Artificial Intelligence, due to their potential for driving higher productivity growth.

A deeper, more nuanced understanding is needed to explore how and why barriers and enablers prevent or facilitate technology adoption across the UK business population. Qualitative work is needed to explore in particular how businesses weigh up and negotiate these as well as the relationships and inter-connectedness between these factors. Insights from this work will contribute to the DCMS/DSIT evidence base on drivers of advanced technology adoption in businesses.

2.2 Research Design

The aims of this qualitative research are to:

Further our understanding of the drivers of business decisions around adoption of new emerging / advanced technologies
Further our understanding of how businesses are experiencing barriers and enablers to adoption and diffusion in more depth, including how these differ according to business characteristics

The scope of this research is to explore the main enablers and barriers to adoption of advanced technologies for UK businesses. The research does not explore what businesses do to improve business-level productivity or growth specifically. The study only explores experiences of technology integration insofar as assumptions about integration affect adoption decisions.

‘Advanced technologies’ is a broad term and there is no universally accepted definition. A working definition was agreed for this project as:

Cutting-edge technologies at the boundaries of existing scientific, engineering and technological knowledge which are likely to integrate elements from domains such as digital technology, data science and analytics, AI, robotics and material science.^{[footnote 1]}

The scope of advanced technologies included for discussion was limited and contained within 5 technology ‘clusters’ (defined in Appendix 2).

The design for this research was iterative, incorporating 2 phases, with collaborative reviews between each phase. The primary research took a qualitative approach in recognition that the complex dynamics and perceptions shaping business adoption decisions cannot be sufficiently understood through quantitative data alone.

The scoping phase involved a literature review and a stakeholder workshop. IRC academics from the University of Warwick conducted a systematic review and identified 40 articles to summarise the existing evidence. Findings from this review informed the design of the primary research. A 2-hour online workshop with government stakeholders helped to finalise the design of the primary research.

The primary research involved 80 UK business interviews. These were one-hour semi-structured interviews, conducted online through Microsoft Teams. 8 of the interviews were deep-dive case studies with 2 participants designed to gather multiple perspectives on decision making within a business.

To supplement this insight with a more holistic perspective on sector and technology specific barrier and enablers, 8 stakeholder interviews were conducted with those who had varied roles in facilitating adoption of advanced technologies.

The business interviews were conducted with decision makers or those with knowledge of their business’ decision-making process for advanced technology adoption. 3 primary quotas were set as these characteristics were expected to inform barriers and enablers to adoption: sector, business size, and level of technology adoption. 5 sectors were included: Manufacturing, Retail, Finance, Creative industries, and Professional, Scientific and Technological services (Professional services). These were selected to provide breadth to the research. The 8 stakeholder interviews included a range of participants with expertise either in specific advanced technologies of interest, or technology adoption within the 5 sectors included in this research. All participants were identified and invited to take part through free-find recruitment techniques. A full achieved sample frame can be found in Appendix 4.

Given the volume of rich detailed qualitative data produced, and need to manage the data systematically and rigorously, a framework approach to analysis was undertaken. Key themes were identified through the use of creative brainstorming sessions. The thematic analysis was supplemented with the creation of a typology to identify distinct business segments across the sample. The segments were hypothesised and then validated against each case in the framework and refined.

Whilst a high-level summary has been provided here, the detailed methodology - including the full list of research questions, sampling criteria, and information about the analysis approach - can be found in Appendix 1.

Question 3

3.  Catalysts and constraints: key factors driving business adoption decision-making

Accepted Answer

This chapter reports on the barriers and enablers, or catalysts and constraints, to advanced technology adoption identified across the business sample.

3.1 Exploring the system

Building on the literature review^{[footnote 1]}, this research confirms that business decision-making on advanced technology adoption is complex and that decisions are shaped by the dynamic interplay of multiple interrelated factors. There was no single most influential determinant of decisions. Instead, businesses reported experiencing multiple catalysts and constraints which act with varying degrees of strength as push and pull forces on their decision-making.

The terms ‘catalyst’ and ‘constraint’ present a more accurate reflection of the discussions than ‘barriers’ and ‘enablers’ which convey a sense that factors are more deterministic. Instead, we found that all of the factors reported here were part of dynamic evaluation practices by businesses.

Catalysts encouraged a decision to adopt. While stronger catalysts were seen to drive the decision, weaker catalysts played more of a supporting facilitative role.
Constraints were factors which could prevent adoption. Stronger constraints acted more like barriers, whereas weaker factors were seen to create resistance to be negotiated in the decision-making journey.

The catalysts and constraints reported were opposing sides of a set of key factors (e.g. either having or not having the requisite skills).

This chapter is primarily structured by a Systems Approach and sets out the universe of factors at play, as is illustrated in Figure 1 below. In line with the Technology-Organisation-Environment (TOE) Framework^{[footnote 3]}, factors emerged at the level of the technology, organisation, and wider external levels. The relationship between these 3 levels is nested and the outer levels influence the internal ones, but all levels and factors influence the adoption decision. It is important to note, as is explored throughout this chapter, that these factors inter-relate, within and across the 3 levels. Whilst ultimately dynamic interplay between the factors drives adoption decisions on a case-by-case basis, we first need to understand the system.

Table 2: Outline of the 19 factors

Level	Factor
Technology	Clarity and relevance of use cases
Technology	Technology risks
Technology	Systems alignment
Technology	Perceptions of usability
Organisation	Affordability (cost vs Return-on-Investment ROI)
Organisation	Access to skills
Organisation	Leadership attitudes
Organisation	Business risk profile
Organisation	Strategy/strategic ambitions
Organisation	Presence of supportive structures
Organisation	Alignment with brand values
Organisation	Employee attitudes
External	Standards and regulation
External	Shareholder/investor pressure
External	Competitor dynamics
External	Customer dynamics
External	Supply chain dynamics
External	Sector norms
External	Access to trusted advice

Figure 1: System level with 19 factors

Overall, business risk profile, clarity and relevance of use case, affordability, and regulation were widely reported to play a key role in adoption decision-making.

Figure 2: Reporting of factors across the sample

Business decision-making: Willingness, Capacity and Capability model

However to better understand how these factors influence decision-making, we also need to consider the decision-making dynamics that occur within businesses, where adoption decisions are ultimately made. Factors become relevant, and influential, at different points in a business’ decision-making process. This model, set out below in Figure 3, identifies 3 stylized categories to this process – willingness, capability, and capacity^{[footnote 4]} (WCC). In this chapter, we examine which categories the factors most meaningfully exert influence on. Whilst all of the categories were important, more of the factors identified were associated with willingness.

Figure 3: Willingness, Capability, and Capacity model

Category 1: Willingness to consider a technology.

This encompasses appetite and openness to considering a technological solution, which is shaped by attitudes and expectations related to potential benefits (and costs) to the business. Note that this is not willingness to adopt the technology but a willingness to consider a technological solution to a problem in the first place.

Category 2: Capability to implement change.

This refers to the degree to which willing businesses are able to adopt innovations with the resources they currently have or are able to access (either by acquiring new resources or using external ones). We think of adoption capability as resources across categories such as financial resources, technical skills, management skills, strategic planning, etc.

Category 3: Capacity to devote resources.

This is the ease with which willing businesses with the requisite capabilities can direct and devote resources to technology adoption at a particular moment in time. There may be competing needs that mean existing capability is engaged in other aspects of the business (e.g. skills or budget need to be used elsewhere). As such, this evaluates how businesses plan for, balance, and perceive the opportunity costs of technology adoption.

While in reality decision-making does not unfold in neatly defined sequences, it is helpful to think of these categories as a series of decision points or gates. All of the categories need to be sufficiently satisfied to a certain degree for an adoption decision to proceed and significant constraint in any one category can cause a blockage. We argue that first a business must be willing to consider new technologies as part of their strategy or as a response to a specific problem. Secondly, they must have the capability to implement the technology. Finally, the business must perceive that it has the capacity to devote the resources it has to implementation and to weather change to achieve expected returns on investment.

This approach highlights that adoption decisions do not typically proceed or stall because of a single factor but rather are usually influenced by a constellation of considerations across the categories. The WCC approach enables us to explore how constraints can accrete across willingness, capability, and capacity. It complements the systems perspective and the 2 approaches together help provide a fuller and more nuanced understanding of businesses decision-making.

This perspective adds value by enabling a more nuanced understanding of the different points at which decisions to adopt can fail, which can help underpin more appropriate interventions (discussed further in chapter 5).

3.3 The 19 factors

This chapter now focuses on each of the 19 factors in turn and for each identifies its relative importance, describes how it can act as a catalyst or constraint, explores its relationships with other factors, and where and how in the WCC model it exerts influence. Within each level, the factors are broadly ordered by how commonly they were reported as relevant and important by businesses across the sample.

Technology factors

This section explores 4 technology level factors. It is important to note that it is business perceptions of these features and characteristics that are important.

Clarity and relevance of the use case to the business

This was one of the most commonly reported factors across the sample and regarded by many businesses as central to adoption decisions. It refers to the extent to which businesses could understand a technology’s use case and perceive it as relevant and to provide benefits and add value to their specific business. The relevance of a technology was also shaped by the route to adoption and whether it was for a specific project or on-going use.

This factor was a strong catalyst when the use case was clear and presented accessibly to businesses and they could clearly see how it could add value to their specific business.

It was most powerful when the use case addressed an immediate or recurring problem.
The most appealing use cases were to: increase sales; reduce direct costs; increase efficiency, productivity, speed or accuracy; enable new or enhanced products or services; improve customer experience; or contribute to sustainability efforts.
Some Innovators saw adoption as an end in itself and were more prepared to experiment with technologies to see how they could be useful to the business later even if there was not an immediate specific use case.

Meanwhile a lack of clarity of use case could serve a strong constraint when businesses could not see what benefits a technology could bring to them specifically. This factor is particularly important for advanced compared with more established technologies as there is lower awareness and understanding and fewer examples of application, particularly in smaller businesses and more traditional sectors. This was problematic for some advanced technologies where benefits were less tangible and therefore it could be harder for businesses to visualise the value.

“I didn’t really understand until like the second or third time I’d seen it [what it could do] … then I just started playing around with it … this is really something new and different. Like this is quite powerful!”

(Retail, Small)

Relationships between the factors

The key relationship of clarity and relevance of the use case to the business was with skills and the extent to which business’ had access to technical skills and knowledge internally or externally to help them understand and apply use cases to their business. It also overlaps closely with affordability as the more businesses bought into the benefits of a technology, the more able they were to calculate ROI and make a business case for adoption. Clarity of use case also overlapped with strategy and the extent to which businesses could see how a technology could contribute to their strategic ambitions and brand values. Understanding the benefits of a technology was also strongly interrelated with technology risks when businesses came to weigh these against each other.

Influence on Willingness, Capability and Capacity

This factor was widely thought to strongly exert influence on willingness to adopt as businesses are more likely to be open to a new technology as a solution or opportunity if they understand what benefits it can contribute to their business. Without this, businesses were unlikely to be willing to adopt a technology, particularly if they were not aware of the technology, its benefits, and its value to them specifically.

Technology Risk

Technology risk was quite commonly mentioned as a constraint. This was strongly linked with clarity of the use case as businesses needed to understand not only the benefits but also trust that the technology could deliver them and the promised functionality and lack of trust could diminish the power of the use case.

Some businesses were sceptical about whether advanced technologies are mature enough to deliver their promised functionality. This factor is again particularly problematic for advanced technologies compared with more established technologies as there are fewer working examples and evidence of trialling and testing available to drive business confidence.

“We are such a data driven industry, and therefore for us, accuracy is very important, because even a point, point 1% here and there can basically derail everything. So precision is very, very important. “

(Finance, Large)

A number of factors could affect business confidence in promised functionality.

Salespeople, advisors and consultants could play an important role, with reliable and impartial advisors helping to boost confidence and those who gave the impression of over-selling sometimes putting businesses off adoption.
Previous experiences of adopting and implementing advanced and established technologies were cited as playing a role.

Relationships between the factors

Technology risk’s most important relationships were with clarity of business case and affordability because concerns about functionality could affect ROI calculations. Access to skills was important as this affected business’ ability to confidently assess functionality risks. Business risk profile played a role as this shaped how prepared businesses were to take on and manage these risks. Access to trusted advice was important as external advisors could help to boost business confidence that they could identify and manage these risks. There was also an important overlap with regulations because functionality risks could affect how confident businesses were that they would be compliant.

Influence on Willingness, Capability and Capacity

Technology risk was widely thought to exert influence on willingness to adopt because concerns about functionality shape how attractive a technology is as an opportunity or a solution to a problem. This factor also exerts some influence on capability and capacity, in so far as businesses were imagining how poor functionality could affect their ability to deliver to clients and customers.

System alignment

System alignment was quite widely reported to be an important consideration.

Poor system alignment could prove to be a “stumbling block”, but for most businesses this was a consideration which created resistance rather than a strong constraint. Discussions about alignment could be based on assumptions rather than accurate facts. The main way it acted as a constraint was through the costs associated with alignment and the consequent impact on ROI, particularly if alignment required change and disruption to business processes.

It was commonly raised by larger businesses and those doing more trialling and testing, but these businesses were also more able to overcome this constraint when they were bought into the value of a technology.
It was a more prominent issue for global businesses who needed to ensure alignment across different markets.
Adaptability of the technology was raised by some more agile businesses who were more comfortable with constant technological evolution and therefore needed technologies to be able to adapt and align with their evolving systems in the future.

System alignment was rarely raised as a catalyst but we can extrapolate that reassurance about alignment could serve to be facilitative. In general, businesses found it easier to adopt new technologies which could easily “bolt on” to their existing systems.

Relationships between the factors

System alignment strongly overlapped with skills and how able businesses were to assess alignment and manage integration. There was strong overlap with Affordability as alignment work could increase costs and affect the ROI calculation. It relates to use case as poor alignment can lessen the power of the use case. It also relates to technology risk as poor alignment could affect functionality. Access to trusted advice could help businesses negotiate this constraint. It could also overlap with client and supplier dynamics if alignment with these organisations was required (which could serve as a catalyst or constraint accordingly).

Influence on Willingness, Capability and Capacity

Perceptions of how easily a technology can integrate into systems and processes can affect willingness because it will affect how disruptive implementation is seen to be. System alignment can influence capacity, where significant effort is required to achieve alignment and particularly if this requires downtime in Manufacturing.

Perceptions of usability

Usability was mentioned by some businesses, particularly those with lower skilled and/or aging workforces. As with system alignment, this could often be about perceptions rather than accurate experiences. Whilst perceptions of user friendliness could serve as a weak facilitator, usability was most commonly reported as a constraint.

“Over the last couple of years they’ve been quite intimidating. That has put people off.”

(Creative industries, Small)

Usability was more important when a technology would be customer facing, than concerns about poor customer experience could be a blocker. Customer facing interfaces needed to be “aesthetically pleasing” and easy to navigate.
When for internal business use, perceived poor usability could raise concerns about the time and resource that would be required for training. This could mean it could take longer for businesses to realise the benefits and the potential ROI. Perceived poor usability could diminish the use case (particularly if it was to increase efficiency).

Relationships between the factors

Usability strongly overlapped with system alignment and how easily a technology was seen to work with current systems and processes. It also overlapped with use case as benefits may not be delivered if staff struggled to use the technology. It overlapped with skills (as more highly skilled businesses were more confident they could implement and use a new technology and more quickly) and affordability as effectiveness of staff use could impact ROI calculations. There was also strong overlap with employee attitudes as staff who were more bought in to the value of new technologies would be more engaged with learning to use them.

Influence on Willingness, Capability and Capacity

Perceptions of usability can affect willingness because again it will affect how disruptive integration is perceived to be and how long it will take staff to learn to use the technology could affect how long it takes for the business to see ROI. Whilst the connection was weaker, perceptions of usability could also impact capability, as this may affect how ready businesses think they are for adoption with their current staff and their skill levels. Assumptions about how much time for training would be required could also impact how much capacity businesses think they have for implementation.

Organisation-Level Factors

This section explores 8 organisation level factors. It was commonly reported that business culture is a key driver of adoption, and that some businesses “are more innovative” whereas others are more resistant to change. Analysis suggests that in these assertions about business culture, participants were bundling together factors and that this “business culture” referred to comprises of a combination of internal factors which collectively form a powerful driver of adoption. Understanding that these combined internal factors play a key role can help us to understand why businesses operating in the same markets make different adoption decisions about the same technologies.

Affordability

Affordability was mentioned across every interview and emerged as a strong constraint. This factor refers to how affordable a technology is perceived to be, meaning how its costs weigh against the potential ROI. In many cases it can be difficult for businesses to assess affordability due to limited information about potential costs and ROI, particularly where benefits of a technology are less tangible (e.g. efficiency gains).

“It’s purely cost…we would do it now otherwise, because there’s not much of an argument to suggest you wouldn’t.”

(Manufacturing, Medium)

Cost acted as a strong constraint for some businesses, particularly small businesses, and for some this was a blocker they could not overcome. However, it is important to note that direct costs were not assessed in isolation, but with reference to the wider financial health of the business and sector now and in the future.

Initial purchasing and implementation costs were reported to be important across most interviews as well as on-going maintenance and subscription costs. Larger capital investments needed to be considered as part of wider annual or even long-term financial planning cycles. For subscription-based investments there was some concern about being locked into contracts that could increase costs in the future. Some businesses were reassured by trialling and cooling off periods.
Businesses also considered other costs such as the cost of system alignment, advisors and consultants for implementation, time resource for implementation, and time for staff training. Some businesses were also conscious of considering costs of things going wrong.
Businesses were generally looking for the best value from providers, and given the numerous risks associated with advanced technologies, they were not generally looking for the cheapest option but the best value.

Costs were always viewed dynamically and weighed against the potential ROI which could serve as a powerful catalyst. Some businesses were interested in the ROI offered in terms of generating more sales, allowing them increase prices, or creating new offers. More commonly, ROI was created through efficiencies and increased productivity.

For many businesses, other than large businesses with dedicated innovation teams, ROI calculations were often seen to be challenging. This was particularly the case for technologies which claimed to improve efficiency.
Some businesses also considered the cost of non-adoption in their affordability assessments and what the risk was to the business of falling behind competitors.

When there was a clear business case and potential for ROI, businesses could be creative at addressing the cost constraint.

Some businesses were prepared to borrow money to invest
Some businesses described ways they could pass costs on to customers (particularly those operating in luxury and sustainability focused markets or working with high margin and large budget customers such as oil businesses).
A small number of businesses mentioned government grants and subsidies and Research and Development (R&D) tax relief as helping to facilitate adoption, but these avenues could also serve as a constraint where businesses were waiting to see if new options would become available in the future.
Some businesses reported having dedicated innovation budgets and for them, the existence of these was a strong catalyst for adoption because the money was ring fenced and staff often knew they could apply and make a use case for the fund.

Relationships between the factors

Affordability was most closely tied to the clarity of the use case and the benefit the business envisaged and how confident they were this would be achieved. This latter point was, as discussed, highly inter-related with technology risks, system alignment, usability and skills. Affordability was also related to competitor dynamics and whether there could be a financial impact of non-adoption. Business risk profile shaped how willing businesses were to take a risk in investing in new technology when many of these calculations were based on estimates from limited information. Investors could also be relevant to these calculations if they were either investing or involved in the decision-making.

Influence on Willingness, Capability and Capacity

Affordability was widely reported to influence capability to adopt, as businesses needed to either have the resources to afford to buy, implement and maintain a new technology, or be able to identify ways to acquire these. Affordability also exerts influence on capacity as businesses usually (unless they had specific innovation funds) had to make choices about whether to invest funds and whether a new technology would be a better investment than other potential areas. Whilst the connection is weaker, affordability can also influence willingness, where the cost was seen as too high to even consider.

Access to skills

Access to skills was commonly mentioned across the sample. Whether the business had access determined whether this was framed as a catalyst or constraint. Access to skills was seen as facilitative as it could smooth the envisaged pathway. Lack of access to skills was generally seen to create resistance rather than as a barrier, as businesses were generally willing and able to address skills gaps if the business case was strong enough and they could cover the costs of accessing the required skills, for example by hiring staff .

There were 2 types of skills reported as influencing the adoption decision:

Businesses needed the skills required to implement and embed the technology. Where they possessed this in-house, this could facilitate the adoption decision because they had more confidence that integration would be done smoothly. However, many were happy to work with consultants and advisors (including university partners) on implementation and many also expected suppliers to assist with this.

“The complexity of managing a project of that size when it isn’t your skill set necessarily. And that’s why we have to go to consultants to help us because literally, we didn’t know where to start.”

(Manufacturing, Large)

Businesses needed the skills to use a new technology and realise its potential benefits. This could be based on perceptions of skills required. Where this was not seen to be the case, businesses usually needed to consider training costs and time resource. Whilst a consideration, this is unlikely to be a key driver of the adoption decision. Some businesses expected this constraint to be addressed by assuming suppliers would provide training if required.

An alternative was for businesses to employ new staff: developers and other IT staff were seen to possess important skills. Some businesses noted that accessing these skills can be challenging as they are competing globally for relevant skills and talent, and that accessing visas for required software engineers can be a strong constraint.

Relationships between the factors

Access to skills overlapped with affordability when businesses needed to consider the cost of accessing missing skills. However, the degree to which skills were perceived to be missing could depend on perceptions of usability and assumptions about system alignment. As with many of the other factors, access to trusted advice was important as a way to fill knowledge and skills gaps. Skills also overlapped with employee attitudes as this could shape the degree to which staff were interested in learning and therefore the extent to which businesses could expect to realise the benefits.

Influence on Willingness, Capability and Capacity

Access to skills was a key influence on business capability as this shaped the degree to which businesses saw themselves as having the skills required to implement and use the technology and therefore whether it could deliver the anticipated ROI. Access to skills also affected capacity as level of access shaped how able businesses were to move resource from other tasks and deploy the skills they had to implement and use the technology at this time.

Business culture: Business risk profile

Business risk profile was a key contributor to how innovative a business and its culture were seen to be. This was often implicit in the ways that participants described their strategic priorities and decision-making practices, but it was a key factor driving adoption decisions. Business risk profile refers to how willing a business is to take on or absorb potential challenges from adoption, such as high costs, uncertain returns, and technology and regulatory risks. Risk profile is particularly important when it comes to advanced technology adoption due to some use cases being quite intangible and there being less examples of successful implementation available.

Risk profile served as a powerful constraint in businesses that were more risk averse and more resistant to change. They tended to:

Be more cautious about ROI calculations and assumptions about if and when a technology would deliver value.
Be more cautious about technology risks and the damage these could do to their reputation if a technology failed to deliver promised functionality.
Place more importance on regulatory and legal risks which could serve as powerful constraints or even blockers (e.g. risks around data security, safety, quality, and plagiarism).
Have less skills internally to help them assess this collection of risks, whereas those who were risk tolerant were concerned but tended to have greater access to skills and experience to help them assess and manage these issues with more confidence.
Adopt when it is seen as more of a risk not to do so, once many of their competitors had done so.

Meanwhile risk profile could alternatively serve as a catalyst for businesses who had a higher risk appetite and were more likely to be interested in trying new things. Innovators who wanted to be at the front of their industry could even be understood to be risk seeking, if this gave them the chance to get ahead. More often, businesses were risk tolerant and would seek advice and carry out evaluation and risk assessment of the opportunity (with varying degrees of formality). A clear use case demonstrating the value to the business and demonstration of how ROI would be achieved could help with these assessments and tip the decision.

“Part of being an industry leader means embracing new technologies and taking risks and doing things that maybe legacy media companies aren’t doing.”

(Creative industries, Large)

Relationships between the factors

Business risk profile was at the heart of business culture. Risk profile was generally associated with business leaders but participants often also referred to the attitudes of employees across the business and sector. The association with leaders meant this attitude was also cascaded through business strategy and structures. Group membership and investor interests could also influence this profile. Risk profile played a key role in how businesses interpreted use cases and assessed technology risks as well as weighting in affordability calculations. It also shaped how businesses approached ensuring compliance with regulations. However, regulation can also shape risk attitudes of businesses, as those operating in more tightly regulated sectors tended to be more risk averse.

Influence on Willingness, Capability and Capacity

Business risk profile influenced willingness to adopt as this shapes an organisation’s willingness to consider a new technology as an opportunity or a solution to a problem, along with the risks and uncertainties that come with this. It may also affect capacity as more risk averse businesses are less willing to direct and dedicate resources to this area rather than other potentially less risky areas.

Business culture: Leadership attitudes

The level of buy-in from C-suite leaders and the degree to which they prioritised technological innovation was an important factor in adoption decisions across the sample.

Where senior leader buy-in and appetite for innovation was reported, it was seen as a strong catalyst. When technology innovation was known to be a leadership priority, it could be more easily prioritised in cost and resourcing conversations.

“Our CEO is you know it’s his number one thing, it’s what he does. He likes to think about lean technical teams and having less waste.”

(Professional services, Medium)

Conversely, where C-suite leaders or boards were less bought in, this could act as a strong constraint and even blocker. In these cases, it could be difficult for other senior staff to convince a leader to make investments. Other senior staff and innovation champions could become fatigued if they constantly met leadership resistance. In some structures, leaders could be disincentivised to support investing (e.g. in partnership models).

“…. if the pushback comes from those heads of the business … then you’re fighting against a brick wall.”

(Finance, Large)

Leadership attitudes were open to various influences that could shift them:

A new C-suite leader could recalibrate business culture, particularly if they had previous experience of adoption which could help businesses grow in confidence to overcome concerns about affordability, functionality, alignment, or usability.
The scope of particular C-suite roles in decision-making could be influential, for example the degree of involvement of a CFO could shape the degree of focus on costs.
For those part of a Group, their priorities could shape the pace of innovation in the business culture. The Group might also influence decision-making more directly, either by issuing businesses with targets (e.g. sustainability targets) or by providing funding. Alternatively businesses might gain access to tools which have been paid for at the group level (e.g. subscriptions to AI tools).

Relationships between the factors

Leadership is a core component of business culture and is therefore unsurprisingly linked to many of the Organisational factors. Business risk profile tends to be strongly linked to their attitudes as senior leaders often have sign off on costs and make the ultimate affordability decision. Leadership attitudes also relate to employee attitudes as they can give confidence, and business strategy and structures follow their priorities. Senior leaders often tend to be older and more experienced and therefore reflect sector norms and some participants commented that cultures were changing as older leaders retired.

Influence on Willingness, Capability and Capacity

Leadership attitudes were reported to influence business willingness to adopt as they drive direction, priorities and usually have sign off on costs. Leaders can influence capacity where they have the discretion to decide whether resource is allocated. Whilst a weaker connection, individual leaders can also affect capability, depending on their own skill levels and previous experiences of technology adoption.

Business culture: Strategy and strategic ambitions

The degree of alignment a technology was seen to have with business strategy was an important factor across the sample.

Alignment with business goals could serve as a catalyst, although this was not a prerequisite. It was most commonly referenced to goals around reducing costs, increasing efficiency or productivity, or providing a better product or service to customers. In some cases, reducing costs was about replacing people, but many businesses were keen to stress that this was not their aim, and that their use of these technologies was about freeing staff up to do other work or be more productive.

For larger and some medium size businesses, this factor was discussed with reference to alignment with their formal business strategy. For most businesses, this factor was about the degree to which the technology could help them achieve their strategic ambition which did not need to be set out in a formal strategy and was essentially about their growth ambitions, for example:

Market leaders tended to have more of a focus on innovation and placed importance on this to maintain their position;
Some businesses wanted to be seen as innovators and were more willing to experiment with new technology to achieve this;
For businesses looking to grow, new technologies could be a way to bring something new and grow their profile;
Starts ups sometimes saw themselves as “disruptors” and were therefore more open to taking risks to get ahead of competitors;
For businesses struggling to compete and operating in low margin and/or highly competitive markets, adoption could be approached as a means of survival;
Some were looking to shift their position and be associated with higher quality goods and services, sometimes to avoid the race to the bottom, and technology could support these goals.

Meanwhile, more modest strategic ambitions could serve as an adoption constraint for some businesses when they were more satisfied with their client base, market share and revenue generation and not looking for high levels of growth – and were therefore less interested in doing things differently.

Relationships between the factors

Strategic ambitions overlapped most notably with use case and the extent to which this was seen to align with business strategy and ambitions. It helped where the use case used language and terminology which aligned with their strategy or how they understood their mission and goals. Unsurprisingly there was overlap with other elements of business culture such as leadership who set the strategy and risk profile which informed their ambitions. Business strategy also closely overlapped with brand values. Business ambitions were also closely entangled with competitor and customer dynamics which framed what was possible as well as sector norms which could set expectations for businesses.

Influence on Willingness, Capability and Capacity

Business strategy and strategic ambitions most clearly influence willingness to adopt, as this factor created an impetus and motivation to consider new technologies and how they could contribute to business goals. There is some overlap with capacity in so far as business strategy dictates what is prioritised in a business.

Business culture: alignment with brand values

Alignment of technologies with brand values was a consideration for some businesses, and this was closely inter-related with strategy. Technologies that were seen to be able to contribute to and embody brand values were more appealing. For some Innovators, innovation itself could be a brand value in itself.

When a technology was seen to contradict or threaten brand values, this could act as a constraint for businesses because it could negatively affect their reputation with customers:

Particularly for businesses with brand values around sustainability;
Particularly for businesses seen as a reliable and safe pair of hands by their clients, especially where they were concerned about security and privacy.

“So growth is obviously absolutely key for business, but we have to do it not being at the detriment of sustainability piece.”

(Manufacturing, Large)

Conversely, where a technology was seen to support brand values, this could play a facilitative role, for example as further justification in a business case:

For businesses focused on sustainability, carbon reduction technologies could be very appealing (for those seeking to achieve either their own or a client’s net zero targets). 2 businesses said that there is a “moral” imperative for businesses to reduce their carbon emissions and that some of these technologies can help with that.
For some businesses with a focus on inclusivity, advanced technologies could be seen to help with these efforts; for example virtual stores and Virtual Reality (VR) experiences.
For some businesses, these technologies could help to promote their brand more generally, particularly when use might lead to awards or media coverage.

Relationships between the factors

Alignment with brand values overlapped mostly notably with business strategy. There was also overlap with the use case and the extent this aligned with delivering the brand values as well as technology risks when these were seen to threaten brand values. There was also a connection between brand values and customer dynamics, particularly for businesses with a more value driven customer base.

Influence on Willingness, Capability and Capacity

For some businesses, brand values exert pressure on willingness to adopt, depending on the extent to which a technology either aligns or not with its values.

Business culture: employee attitudes

Employee attitudes were not reported to be a strong factor, but were commonly reported to be consideration and could play either a facilitative role or create resistance.

Employee attitudes were sometimes a constraint in less innovation focused businesses:

Negative employee attitudes were most commonly due to concerns about the threat technologies presented to jobs. Senior leaders were concerned that employee resistance could affect ROI if the value of a technology was not maximised due to staff disengagement or even resistance to using or training for it.
In some sectors, there could be more value driven resistance to new technologies; for example, some in creative industries saw AI generated content as “lacking authenticity” and a risk to overall quality in the industry as a whole in the long term. However, creatives who were more bought in to the value of new technologies could see them as “augmenting” their efforts.

“It is still a bit taboo to be using AI too much, especially with games and creative media where you want that human touch and human element.”

(Creative industries, Large)

In more innovation focused businesses, employees tended to be more bought in to and supportive of technology introduction which could serve as a facilitator.

This was particularly the case where employees agreed that a technology could make their job easier or allow them to focus on more rewarding aspects of their role.
Innovation focused businesses tended to have structures and cultures that were more open to ideas being put forward by employees (e.g. regular open meetings). It seems likely that if staff are engaged and involved in adoption decisions then this can help to increase levels of employee buy in.

“Before anything is done in the firm, we try to see that everyone is carried along, everyone knows what’s going to happen. “

(Professional services, Large)

The level of supportiveness of employees seemed to vary with the business and wider sector skills profile; those with more highly skilled roles and employees tended to be more supportive, whereas employees and businesses with lower skill levels and profiles tended to be less supportive. Numerous participants also referenced the age profile of businesses and sectors, with aging workforces tending to be less engaged and supportive of new technologies.

Relationships between the factors

Employee attitudes were strongly entangled with sector norms and leadership attitudes. Employee engagement was inter-related with the use case and the extent to which employees bought in to this or whether the aim was to reduce headcount. This factor was also strongly related to skills and perceived usability. Business structures can affect the degree to which employees were engaged and consulted or could contribute to adoption decisions.

Influence on Willingness, Capability and Capacity

Employee attitudes exerted some influence for some businesses on willingness to adopt, in so far as these shaped assumptions about the degree of engagement there would be with a new technology and therefore how able a business was to get ROI. Employee attitudes also shaped willingness through the degree to which employees proactively engaged with making suggestions. Employee attitudes could influence capacity in so far as this affected how engaged they would be with using a new technology.

Business culture: presence of supportive structures

Business structures can either facilitate or provide resistance to adoption.

There was wide variation in terms of how formalised adoption decision-making processes were, with larger and older businesses tending to have more developed structures and younger and smaller businesses tending to take more agile (or more ad hoc) approaches.
The size of the investment was important, with larger investments requiring more formal assessment, scrutiny, and planning whereas low-cost subscriptions could usually be approved more quickly.
The route to adoption was also important, with project-based requirements being easier to gain approval for.

More formal and hierarchical structures and decision-making processes were usually seen to create resistance.

These approaches often meant more time was required for decision-making because a more thorough business case and risk assessments needed to be developed and passed through multiple approval layers. Enthusiasts could become de-energised if they met resistance within these structures.
However, formal structures could also create opportunities: some large market leaders had innovation focused teams and resource within their structures. Some businesses also held regular open sessions within their processes where ideas could be raised and discussed. Whilst formal and hierarchical structures could create resistance, they could also create a safe, supported and ordered approach to innovation and managing the risks.

Flatter and more agile approaches were often seen to be more facilitative as these removed some degree of formal processes.

However, in smaller businesses, these approaches could mean that single or small numbers of individuals had a high degree of influence and would need to be convinced.
Flatter and less formalised systems could also mean more chaotic and disordered approaches to decision-making which could create resistance.

Whilst structure played a role, what mattered more was the degree of openness within these approaches to technological innovation.

Relationships between the factors

Business structures were highly entangled with the other business culture factors, particularly risk profile and leadership and employee attitudes which were expressed and enacted within these structures. The use case and affordability assessment needed to be passed through these structures where facilitation or resistance could be enhanced.

Influence on Willingness, Capability and Capacity

As discussed, business structures affected how open to new technologies businesses were, and indeed to change more generally. Structures could affect the capabilities businesses had (for example whether or not they had an innovation team) as well as the degree of agility of a business shaped how able it was to move resource around to focus on emerging priorities.

External factors

This section reports on 7 external factors which were seen to influence adoption decision-making. Together 4 of them were seen to collectively exert market pressure on decision-making (competitor, customer and supply chain dynamics and sector norms).

Standards and regulations

Regulation was widely reported across the sample as strongly influencing business adoption decisions, across all sectors, firmographics, and technology clusters (but particularly for AI and environmental technology adoption).

In some cases, regulation served as a powerful and even deterministic catalyst when adoption was seen to be needed to meet compliance requirements. Businesses gave numerous examples of this scenario including:

Where regulation no longer allowed use of current technology (for example because it is not safe or secure enough) or their current technology was not sufficiently powerful enough to meet regulatory requirements (e.g. accurate enough in Finance).
The need to comply with sustainability regulations could force them to adopt new environmental technologies; for example, requirements to report energy consumption, waste disposal and recycling regulations, and emission targets.
For AI, some businesses were aware that employees were using AI tools and therefore wanted to adopt the technology to streamline usage and create policies to ensure employees were meeting legal requirements, especially around data sharing.

“[If] any of these things were forced by actual government regulations, we wouldn’t really have any say in the matter … they may say what you’re using is obsolete and it’s dangerous and if you carry on using it, there’ll be a financial penalty.”

(Manufacturing, Small)

Standards were less commonly raised than regulation. Some businesses said they need to follow standards set by professional associations or sector bodies (e.g. the Law Society) and these could act as catalysts. Standards could serve as a powerful catalyst if these were used in a supply chain, but this was generally raised theoretically by participants.

Regulation was widely reported as a strong constraint when businesses feared their planned use could make them non-compliant. Often this could be a fear of unintentional non-compliance due to a lack of sufficient knowledge and understanding of regulations, rather than knowing non-compliance would be the case. Businesses were afraid of what non-compliance could mean for their reputation or potential legal implications (notably potential fines). This could be particularly “scary” for those with less access to technical expertise and legal advice. Most businesses, other than Innovators, therefore did not want to be the first to adopt in their sector. Businesses gave numerous examples of the ways they feared being non-compliant including:

Not meeting data privacy and security requirements;
Not meeting health and safety requirements
Not meeting quality standards
Violating copyright and intellectual property;
Providing inaccurate information to clients; and
Environmental technologies not meeting planning permission or emission target requirements.

Concerns about meeting regulatory requirements were exacerbated in global businesses exporting to and operating in markets with different rules.

“We always have to put any software through that kind of person [ISO expert] to check that it all kind of aligns with our security and everything […] we can’t use it if it didn’t have those functions.”

(Professional services, Small)

It was rarely the case that businesses thought there was too much regulation for advanced technologies. In most cases, businesses were concerned about a perceived lack of clarity around regulation and this drove concern that they could be unintentionally non-compliant. Businesses said they were often unsure what the regulations were for their specific industry or thought there were not sufficient industry specific regulations in place. This was particularly the case for AI and numerous participants compared current AI regulation with “the wild west” which lowered their confidence to adopt. Many businesses also reported thinking there is a perceived lack of clarity about the government’s net zero targets and requirements and said they think there is insufficient guidance about what they need to do and when. In some cases, they thought planning regulations lack clarity and present issues for environmental technology adoption; e.g. business uncertainty about whether regulations are the same across the UK.

“Particularly in the area of AI there are no kind of recognised ground rules yet because it’s a bit like the Wild West, whereas if you were doing an advert on TV for example, there are reams and reams of regulations and different codes.”

(Manufacturing, Large)

Some businesses were assuming that regulations will change in the near future and were therefore holding off on adoption decisions. There was quite a widespread perception that AI regulations are likely to change in the future and assumptions that these will become stricter, so some businesses were more hesitant about investing larger sums.

“We’ve seen that a lot, we have to pivot to meet regulations that didn’t exist a year ago…they constantly cost us money to do that, eats into our profit.”

(Professional services, Medium)

There was wide agreement among businesses that there is a current lack of standards around advanced technologies, and that this is a constraint because these would serve as guidelines for businesses to feel more confident about how to use advanced technologies safely.

Relationships between the factors

Regulations and standards most notably interacted with business risk profile in terms of how strongly the risk of non-compliance shaped decision-making. It interacted with technology risks regarding how confident businesses were that a technology’s functionality could meet requirements. The cost of ensuring compliance could affect ROI calculations, as well as fears about the potential cost of non-compliance. It was closely connected with skills and the degree to which businesses felt they had the in-house skills to ensure compliance (e.g. legal, ISO, safety, and technical expertise) . Regulation interacted with sector norms in terms of how much sector level guidance and advice was provided and how much adoption existed in the sector to provide examples of effective compliance. There was also an overlap with access to advice for businesses who needed external advice on compliance to boost their confidence.

Influence on Willingness, Capability and Capacity

Concerns about meeting regulatory requirements were widely seen to influence business willingness to adopt – either forcing business to adopt to ensure compliance or driving non adoption when businesses feared non-compliance. Regulatory requirements could affect capacity when resource needed to be deployed to check and ensure compliance. Whilst a weaker connection, regulation could also shape capability to adopt as this affected the policies and procedures businesses needed to have in place to ensure compliance.

Market pressure: customer dynamics

Customer dynamics, meaning how aligned a use case is perceived to be to existing or developing customer demand, was mentioned widely across the sample and could serve as a powerful catalyst.

Customer dynamics could act as a strong or even deterministic catalyst when use was demanded by customers or needed to meet their requirements, for example:

The clearest example was when public sector clients set this out in procurements requirements, particularly around sustainability targets.
Some businesses had experienced specific demands from Business-to-Business (B2B) clients, including clients expressing interest in seeing them use AI.
New technologies could open new markets or help businesses to improve their offer to meet shifting client demands (e.g. VR experiences for creative industries).
For those seeking rapid growth or wanting to scale, advanced technologies were sometimes seen as the best way to help them do that or meet rising client demand.

However, it was more often the case that businesses saw advanced technologies as a way to reduce their costs and pass this on to customers to meet their demand for lower prices rather than them having an interest in the business using an advanced technology specifically.

“They’re demanding in tenders and things like that to use more environmentally friendly material.”

(Manufacturing, Medium)

Customer dynamics could also serve as a constraint. For businesses operating in markets where demand was generally falling, this state of affairs could make it harder for them to justify investment. In more cases, businesses were less clear about what the customer demand is, what they expect and what they are prepared to pay for. Luxury and sustainability focused Retail brands were more confident that they could pass adoption costs on to consumers, whereas lower margin retailers did not believe they could do this. Some businesses had sought to engage customers and clients on this topic, and one manufacturer described some market research they did where customers said they supported sustainability but would not pay 50p more for the product to achieve this.

“… the customer cares about it being environmentally friendly … but at the end of the day, they don’t … care if it’s delivering in a 10-year-old truck or a renewable energy one … They want it for the same price.”

(Manufacturing, Medium)

A small number of B2C businesses believed that use of some advanced technologies may actually put off their customers. This tended to be Retail and Creative businesses where their customer base valued the importance of human connection and interaction, particularly those offering bespoke services or working with more vulnerable audiences.

Relationships between the factors

Customer dynamics closely interrelated with supply chain dynamics (as discussed below) and sectors norms which could set client expectations for the sector. It interrelated with clarity of use case, technology risks, and usability as businesses needed to understand the value to their customers and be confident this would be delivered to avoid reputation damage. There was also overlap with affordability if non-adoption could mean losing clients and falling behind in the marketplace. There was a relationship with brand values for those with a value driven client base. There was overlap with strategy and which clients/customers businesses were either targeting or trying to retain to achieve their strategic ambitions in the marketplace.

Influence on Willingness, Capability and Capacity

Customer dynamics could make businesses more willing to adopt if they are confident their customers want and are willing to pay for goods and services that use more advanced technologies. Customer dynamics can affect capacity when they were willing to pay for the use of technologies and therefore this added resource to the business.

Market pressure: supply chain dynamics

Supply chain dynamics^{[footnote 5]}, whilst not raised by many businesses, could serve as a powerful catalyst when relevant. It closely overlaps with client pressure because, whilst these businesses were not supplying the end customer, the dynamics played out in similar ways.

These dynamics could serve as a powerful catalyst where clients in the chain demanded either use of technologies or requirements which would necessitate usage. Some businesses said that pricing within supply chains could necessitate the use of new technologies to achieve cost savings.
These dynamics could also serve as a powerful catalyst through passive upgrading of contracts, when suppliers automatically updated software or offers, with the most common example being software providers starting to include AI tools automatically. Some suppliers proactively approached businesses and where there was an existing positive relationship, suppliers could act as trusted advisors.
Supply chain dynamics were rarely raised as a constraint. This was mentioned as a minor concern that new technologies may not be accepted by clients further up the supply chain (e.g. a Finance business with reference to use of AI in banking). Some businesses were concerned about post EU Exit supply security of environmental technologies and parts.

Relationships between the factors

Supply chain dynamics strongly overlapped with client dynamics as discussed. There was also overlap with sector norms which set expectations for supply chains. This factor inter-related with system alignment where businesses need to integrate and align with other systems in the supply chain. There was overlap with regulations where all parties in a supply chain need to be compliant and there could be more overlap with standards if more sector-based standards were created. There was also overlap with access to advice where suppliers were seen as trusted advisors.

Influence on Willingness, Capability and Capacity

Supply chain dynamics could exert influence on willingness to adopt when this was a requirement to continue doing business. In cases of passive upgrading, this could influence capabilities if access to technologies was granted automatically.

Market pressure: competitor dynamics

Competitor pressure was widely mentioned as playing some role in decision-making. It was not explicitly reported as a constraint, but analysis suggests that businesses with lower growth ambitions were less interested in technology adoption (this is explored further in the typology in chapter 4).

Competitor pressure could act as a powerful catalyst but was commonly raised as playing a facilitative role. For some Innovators and market leaders, competitor pressure could act as a strong catalyst if they wanted to be seen to be leaders and influential in their marketplace. For most businesses, there was a sense that they needed to keep an eye on competitors to avoid “being left behind”. In some cases, this was because they believed technologies could reduce competitor costs and they would be outcompeted on price. For some, it was that new technology could improve competitor products or services.

“There will come a point where we can’t compete because everyone else is using it [AI]. If we haven’t adopted it by that point, then I think we’ll be pressured to do it purely just to fight for survival financially.”

(Creative industries, Small)

Whilst competitor activity was important, some businesses did not want to end up in “tech debt” just to be in an “arms race” and needed to be confident that a technology would provide them with value beyond just keeping up for the sake of it.

“It’s a bit of keeping up with the Joneses … it’s a bit of a fashion thing, right? A lot of companies, I think they feel that they have to.”

(Manufacturing, Large)

The degree of openness within sub-sectors about what they are doing with new technologies played an important role in how able businesses were to find out what competitors were doing. Some industries were more open and willing to share their experiences at conferences and events. Some businesses were interested specifically in sharing outcomes of trials and experiments to improve overall industry use of new technologies. However, this was not always the case, particularly in more competitive sectors.

Relationships between the factors

Competitor dynamics overlapped with sector norms in terms of these providing expectations. It also overlapped with customer dynamics in terms of businesses working out how to best serve consumers. It strongly overlapped with strategic ambition in terms of how businesses wanted to position themselves against competitors and with affordability in terms of what the cost of non-adoption in the marketplace could be.

Influence on Willingness, Capability and Capacity

Competitor dynamics were seen to be an important influence on willingness to adopt, either to keep up with competitors and avoid falling behind, or as a way to fulfil growth focused strategic ambitions or to lead the market. There was some link with capacity in the sense that the risk of falling behind could influence the capacity decisions businesses made.

Market pressure: sector norms

Some businesses referenced ways in which norms in their industry or sub-sector influenced their decisions. This was often implicit in discussions about their strategic ambitions. Sector norms were more powerful for those operating in sectors at either end of a spectrum of engagement with technological innovation. For those in the middle, this factor strongly overlapped with other market pressures and leadership and employee attitudes.

Sector norms acted as a strong constraint for businesses operating in more traditional sub-sectors where advanced technology adoption was less common; for example, legal businesses.

Businesses felt there was less expectation on them to adopt from customers and competitors.
In general, there tended to be lower awareness and knowledge of advanced technologies and the potential benefits to the sub-sector and particularly to smaller businesses who could see this kind of technology as “not for them”.
In these sub-sectors there was a lack of relevant examples of successful adoption.
These businesses tended to have less technical skills in-house and therefore lower levels of confidence regarding implementation and usage, particularly when usability was perceived to be difficult.
These tended to be older and more established sub-sectors with older businesses, and leaders and employees tended to be less engaged and supportive of new technologies and therefore there was a lack of leadership to create impetus.
Businesses were more likely to have lower growth ambitions.

“5 years ago…nobody was very interested in it. It’s [wealth management] very much an old man’s industry…They don’t like the idea of change.”

(Finance, Small)

Meanwhile conversely, sector norms could act as a strong catalyst for businesses operating in (notably digitally led) sub-sectors where innovation was normalised and vital to the way businesses operated; e.g. Fintech and technology based Professional services.

These tended to be newer sectors and often younger and more agile businesses. As technology tended to be part of their product, budget for adoption was more often baked into financial planning.
There was a strong overlap with competitor dynamics as businesses felt pressure to keep up with the industry and some sub-sectors were used to constant technological innovation as a way of doing business.
There was also strong overlap with customer dynamics in these sub-sectors as use of advanced technologies was expected from their customers for product or service delivery and customer experience purposes.
There was strong overlap with leadership and employee attitudes as both were bought into the value of new technology to business success. Therefore, it was normal for senior leadership to prioritise time and investment for new technologies and for employees to more enthusiastically engage with it.
These sub-sectors tended to have more in-house technical skills.

Overall sector norms were highly self-reinforcing as in sectors where adoption was more normalised, businesses had greater awareness, knowledge and experience of advanced technologies and therefore greater confidence in making adoption decisions about them.

Influence on Willingness, Capability and Capacity

For some businesses, sector norms could exert a strong influence on business willingness to adopt as described above. Whilst a weaker connection, sector norms could also affect capacity in the sense that they shaped the level of skills in businesses across the sector.

Shareholder and investor pressure

Some businesses faced pressure from their own shareholders and investors which influenced adoption decisions, particularly those who had private equity investors. Whilst this was reported by a small number of businesses, it could act as a powerful force when relevant.

Investor pressure could act as a constraint where investors were looking to extract quick ROI which limited business ability to invest in new technologies at that time. Alternatively, it could be that private equity investors rejected adoption of new technologies when they did not think there would be sufficient or rapid enough ROI.
Investor pressure was more commonly reported as a strong catalyst when investors pushed businesses to adopt in attempts to drive growth and profitability. Investor investment could be tied to demands for rapid ROI which could lead to questions about the long-term use of technologies. Some investors exerted pressure related to their strategic interests (e.g. sustainability). In some cases, investors could be motivated by a drive to see more innovation for its own sake.

“Our private equity owners have made it clear that this is what they expect of their portfolio companies. We should be on the path to net zero carbon emissions and so kind of it’s becoming a pressure on the organisation.”

(Professional services, Large)

Relationships between the factors

Whilst this has been positioned as an external factor, there was strong overlap with the organisational level, particularly with business strategy which investors could influence and leadership attitudes when leaders needed to enact investor demands and interests. There was also overlap with sector norms, although investors could be seen to be trying to challenge these. Investment from investors could shift affordability calculations towards adoption and investors could also seek to shift business risk profiles away from risk aversion.

Influence on Willingness, Capability and Capacity

As with the market pressures, investor pressure could influence business willingness to adopt where they expressed a preference either for or against this. Similar to customers, investors could also influence capability when they were prepared to invest money in new technologies. Whilst a weaker link, similar to leaders, investors could also influence capability when they brought skills and experience of technology adoption to the business.

Access to trusted advice

Level of access to trusted advice affected how able businesses felt to make a sufficiently informed adoption decision. Where this factor was relevant, it could be a powerful facilitator, particularly for businesses who lacked internal knowledge and skills.

Access to trusted advice had helped to facilitate adoption decisions when it helped businesses feel more confident they were choosing the right product and that implementation would be smooth. Businesses reported valuing bespoke advice about technology benefits, trustworthiness of promised functionality, ROI they could expect to achieve, and how to manage technology risks and meet regulatory requirements.

Advice could come from a range of sources but it was important that businesses trusted this advice.

For large businesses, trusted expert advice came to decision-makers from their internal specialists; e.g. innovation, IT, legal, compliance, and information security teams. Some businesses sought or received advice from their Group or investors.
Some businesses sought trustworthy external advice.
- In some cases, trust was gained because the source was seen to be impartial (e.g. universities).
- Consultants and advisors could be trusted due to their expertise. Consultants played a key role for some businesses who did not have skills in-house and where they would play a role in implementation. Some businesses could not afford consultants, and a small number were concerned about them overselling or lacked trust because they had had poor previous experiences of implementation with advisors.
Suppliers were sometimes trusted advisors and expected to help with implementation, system alignment, training, and on-going support - particularly where a trusted relationship was already in place.
Some businesses relied on free advice from a range of organisations including trade bodies, professional associations, conferences, trade shows, peer networks and events, and chambers of commerce.
Some small businesses appreciated talking to other small businesses in local business forums.
There was some reference to participants doing their own research and using trade publications and adoption guides, but they could find it difficult to navigate information and know what to trust .

At this stage of the interviews, most businesses said they would not see government as a source of advice on advanced technology adoption (see also chapter 5). Generally, businesses would only look to government for information about regulations and then often said they found navigating websites and information difficult. Some were open to receiving government advice, especially if they could also access grants or funding. However, others rejected this idea where they did not see government as sufficiently knowledgeable, especially Innovators who saw themselves as being ahead of government in this area.

Relationships between the factors

This factor overlapped most notably with skills and business risk profile as discussed. Trusted advice inter-related with use case as it could help to make the benefits clearer to the business and with technology risks, regulation and alignment as they could alleviate concerns in these areas. It also related to affordability as trusted advice could help businesses to feel more confident in their assessments. Access to advice also overlapped with sector norms as these could affect how open businesses were to sharing experiences in peer networks.

Influence on Willingness, Capability and Capacity

Access to advice could influence business willingness as when businesses trusted the source, it could help them to understand the benefits and alleviate their concerns about a range of functionality, financial, and regulatory risks. However more importantly, access to external advice could boost business capability when this was not available and presenting a blocker internally, particularly regarding the implementation phase.

3.4 Willingness-Capability-Capacity Summary

Throughout this chapter we have discussed where and how the factors exert influence on business willingness, capability and capacity to adopt. Table 3 below provides a summary and a more detailed version of this table if provided in Appendix 5.

Table 3: Alignment of the factors with Willingness, Capability and Capacity

	Willingness	Capability	Capacity
Clarity of use case and value	X
Technology risk	X
System alignment	X		X
Perceptions of usability	X
Affordability		X	X
Access to skills		X	X
Business risk profile	X		X
Leadership attitudes	X		X
Strategy / strategic ambitions	X		X
Brand values	X
Employee attitudes	X		X
Presence of business structures	X	X
Standards and regulations	X		X
Customer dynamics	X		X
Supply chain dynamics	X	X
Competitor dynamics	X		X
Sector norms	X
Investor pressure	X		X
Access to trusted advice	X	X

Question 4

4.  Applying lenses: understanding variation in business experiences across the sample

Accepted Answer

The importance of the factors outlined in the last chapter was not uniform across the sample. This chapter explores more systematically how business experiences of catalysts and constraints varied across technology clusters, sectors, and segments. A set of case studies housed in Appendix 6 brings to life the diversity of experiences across the sample.

4.1 Variation across technology clusters^{[footnote 6]}

For information and communication technologies (cluster 1)

A key catalyst was clear efficiency and cost reduction-based use cases. Competitor pressure also played a key role as some businesses felt they have no choice but to embrace these technologies, with the adoption of AI in particular described as a ‘gold rush’.
Key constraints to adopting technologies within this cluster included a lack of trust in promised functionality, lack of internal skills for implementation, and regulatory uncertainty and coupled with the pace of change in this area.

For advanced computing technologies (cluster 2)

The main catalyst was clear use cases focused on increasing efficiency, productivity and speed and reducing costs in the long term.
Key constraints in this cluster were purchase, implementation and maintenance costs which were seen to be particularly high. Systems alignment was also an important consideration, as businesses needed to think about space and integration with systems and processes.

For advanced manufacturing and materials (cluster 3)

Alignment with business strategy and goals was a key catalyst. For some businesses, these technologies were seen to potentially help support their environmental credentials. In addition, efficiency and cost reduction-based use cases were important along with technologies that could improve customer experience.
Although the main constraint was cost, a lack of knowledge about what technology is available in this area was also apparent across the sample.

For Energy and Environmental technologies (cluster 4)

The ability to demonstrate their commitment to sustainability was the key catalyst for businesses. For some businesses adoption was expected from customers and supply chains and for some it was part of their strategy and/or brand values. Some businesses who had adopted these technologies had received government grants which had facilitated adoption.
However, regulatory requirements acted as a key constraint, with some businesses reflecting on how current legislation disincentivised their business from acting. Insufficient UK infrastructure was also noted as a constraint.

4.2 Variation across sectors

Some factors played a more prominent role than others across the 5 sectors included in this research. For each sector, there was a complex interplay of factors shaping decisions although market pressures cut across industries.

Manufacturing

These businesses tended to be most interested in AI, robotics, manufacturing technologies, advanced materials, and energy and environmental technologies.

The main catalyst was clear use cases focused on efficiencies and cost reduction as these businesses usually operated with clear cost per unit models. This was important in the context of businesses facing lower demand and rising costs. Regulatory requirements and market pressures were also important catalysts, particularly in relation to sustainability targets due to the extent of emissions the sector produces.
Meanwhile the main constraints were costs and the costs of system alignment (including operational disruption). Any proposed changes to the factory or warehouse would have to fit with their manufacturing and upgrade cycles. Some businesses also reported employee resistance as an issue.

Retail

These businesses tended to be most interested in AI, robotics, 3D printing, and energy and environmental technologies.

The main catalyst was use cases focused on improving efficiency, driving sales, and improving customer experience.
The main constraint was affordability. Retail businesses were often operating with narrow margins and usually didn’t want to increase costs for customers. This was compounded by a lack of market confidence and concerns about economic volatility. Some were concerned about the potential impact on jobs and the risk of redundancies.

Finance

These businesses tended to be most interested in technologies in Cluster 1.

A key catalyst was clear use cases focused on speed, precision and efficiency. Finance businesses were more likely to adopt if other organisations that they worked with had (e.g. banks) and therefore sector norms and supply chain dynamics were important factors. Meanwhile, internally, many were faced with a lack of knowledge about the capabilities of advanced technologies and a culture resistant to change, particularly among leaders.
Externally, regulation was seen as a key constraint, with businesses reporting that they were limited in what technology they can use by regulators.

Professional services

These businesses tended to be most interested in AI, Future computing and data management and future telecoms.

A key catalyst were use-cases focused on automating non-billable administrative tasks, allowing diversification of revenue streams, or operation outside of office hours. Competitor pressure played a key role in this sector with businesses feeling they need to “keep up”.
However, system alignment was a key constraint as many businesses said they were limited in what systems they could use by the client, supply chain, partner or associated organisations that they are required to work with (for example, the police, courts, banks). Technology and regulatory risks also played a key role due to concerns about security of the personal and sensitive data that they often handle.

Creative businesses

These businesses tended to be most interested in AI, Extended Reality, 3D printing and energy and environmental technologies.

The main catalyst was a response to market pressure and a sense that they will get left behind if they don’t adopt. Some felt that if they adopted advanced technology that they would be able to own the narrative around it and were less likely to be replaced by it. Clear use cases around new products and offers were also important as well those improving customer experience.
In terms of constraints, creative businesses often expressed concern about losing creative control or damaging their reputation by using advanced technology, so were careful to strike a balance between adoption and retaining a human touch in their work. Many also raised regulatory concerns, particularly around use of AI and intellectual property.

4.3 Variation across key segments in the business population

Patterns of business experiences emerged which were more nuanced than being driven by sector alone. This section presents a typology with 6 types to help enhance understanding of the variation in experiences across the sample. This typology focuses on explaining likelihood to adopt advanced technologies. The 2 strongest drivers of this variation were:

The level of buy in to the value of advanced technologies to their strategy
The business risk profile.

This is illustrated in Figure 4. In addition, there was variation across the following factors:

Level of resources to dedicate to technology adoption
Level of business ambition to grow in their marketplace
Level of market pressure from clients, competitors, supply chain and sector
Level of agility in terms of how open business structures and processes are to change.

Figure 4: Key variables driving the typology

The characteristics of each type in the typology is summarised in Table 4 below and each type is described in detail below.

Table 4: Typology: summary of key characteristics

	Pioneers	Strategic adopters	Pragmatic followers	Reluctant adopters	Tech resistors	Detached traditionalists
Likelihood to adopt	Very high	High	Medium high	Medium Low	Low	Very low
Level of buy in to the value of advanced technology to their strategy / mission	Very high	High	Medium	Medium	Low	Very low
Attitude to risk	Risk seeking	Risk tolerant	Risk tolerant	Risk averse	Highly risk averse	Risk tolerant
Level of resources to dedicate	High	High	Medium	Medium low	Low	Low
Business ambition to grow	Very high	High	Medium	Medium low	Low	Low
Market pressure	High	Very high	Medium	Medium low	Low	Low
Level of agility	High	Medium low	Medium high	Low	Medium low	Medium
Key typical firmographics found in the segment (most common characteristics)	All sizes; Start ups / young businesses; technology focused; Finance, Professional services, Creative industries	Large size; Retail, Manufacturing and Professional services; tended to be older and market leaders; part of groups and exporters	Small and medium; all sectors	Small and medium sizes; Retail, Creative industries and Professional services and Manufacturing	Small; Finance, Creative industries; legal; tend to be older	Small; Manufacturing or Retail

Pioneers

These businesses are typically young, agile disruptors as well as leading technology focused businesses.

Business leaders and employees are bought into the value of advanced technology and are actively looking for technological innovation as this is seen as key to their mission and strategic ambitions to grow in the marketplace.
Being innovative is a core part of their business identity and brand. They often want to disrupt the market and grow quickly or need to be highly technologically innovative to maintain their market position.
Businesses are comfortable experimenting with new technologies, and some are happy to adopt technology for its own sake rather than requiring a detailed and specific business case. They are comfortable being first and early adopters in their sector.
They have dedicated budgets and sometimes dedicated R&D teams for technology adoption and inhouse development.
They tend to be operating in highly competitive marketplaces.
They tend to be highly agile businesses, comfortable with change to support their growth mission.

Considering the WCC model, these businesses already have high levels of willingness to consider technology, understand clear use cases, and have capacity in resource-oriented towards this end, for example through dedicated innovation budgets. They are less likely to consistently have capability (in terms of additional resource, skills and time) available to enable them to adopt new technology. Case study 6 in the Appendix illustrates the key findings for this business type.

Strategic adopters

These businesses are typically older than Pioneers and market leaders.

Business leaders and employees are mostly bought into the value of advanced technology and see it playing an important role in their strategy and brand (but there may be some frontline employee resistance).
They need to innovate to maintain their market position. As market leaders, they prioritise having the best technology over being the first one.
Businesses need a clear business case for adoption and tend to have rigorous formal risk assessment and testing processes in place.
They have significant innovation budgets and often dedicated innovation teams. Some also have collaborations with leading global technology businesses.
They tend to be operating in highly competitive marketplaces.
As they tend to be larger businesses, they have more significant structure and process-based constraints to adoption and implementation requires careful consideration.

In relation to the WCC model, these businesses tend to have high levels of willingness in terms of being bought into technological solutions and capability in terms of resource, budgets, dedicated team and staff. Of the 3, they are most likely to face challenges around their capacity to re-direct staff to new technology solutions due to time constraints. Case study 7 in the Appendix illustrates the key findings for this business type.

Pragmatic followers

These businesses tend to be medium sized and often project based with multiple revenue streams.

There is some buy in to the value of new technology in the senior leadership, but it is not seen as core to the survival of the business.
They prioritize staying updated with innovation rather than pioneering it. Instead of actively seeking technological advancements like Pioneers and Strategic adopters, they take a more passive approach - being ‘open to innovation’ rather than actively ‘searching for innovation’.
Innovation is usually seen as a way to improve business performance and a way to move with the times but not integral to success or business identity.
A clear and specific use case is required that addresses a pain point or project need.
Small innovation budgets are available (e.g. for subscriptions).
They are ambitious to grow in their marketplace, but advanced technology is not seen as central to this.
Their marketplace is competitive and there is some demand for innovation from clients and competitors or suppliers. Innovation is often led by the Pioneers and Strategic adopters in their sector.
As project-based businesses, they tend to be quite agile.

Compared to the previous segments, these businesses have medium levels of willingness, capability and capacity to adopt a technology. While understanding the general value advanced technology (willingness), they are most likely to need direct encouragement from the market or leadership to sufficiently consider this technology, have more limited skills and knowledge, and less likely to have innovation-specific budgets. Case study 8 in the Appendix illustrates the key findings for this business type.

Reluctant adopters

These businesses tend to operate in more established markets and have less diverse revenue streams than Pragmatic followers.

There is some buy in to the value of new technology in senior leadership, particularly where it contributes efficiencies/cost savings. However, implementing innovation is usually a reaction to competitive market forces (for example, in order to keep up or to continue to be successful rather than a proactive strategy).
There is often resistance among older frontline workers or senior leadership.
A clear cost and ROI focused business case is required and detailed risk assessment processes are in place.
They tend to be quite risk averse, particularly regarding investment.
These businesses often do not have dedicated budgets and would need to borrow or re-structure funding.
They often lack knowledge and expertise.
They need to grow to survive but are not seeking to lead the sector.
Their marketplace tends to be old, competitive but steady and reliable.
Businesses face significant structure and process constraints.

In relation to the WCC model, these businesses appear to have particularly low levels of capacity, due to the lack business orientation or leadership desire to devote resources towards new technology and medium/low willingness due to lack of clarity on use case. They might possess relevant senior resource relating to specific strategic priorities, but their capability in the form of relevant skills is more limited. Case study 9 in the Appendix illustrates the key findings for this business type.

Technology resistors

These businesses tend to be older, smaller and Professional services businesses.

There is a lack of buy in to the value of advanced technology across the business and it is not seen to be needed for the business to deliver its core mission. This is either due to internal factors such as ‘old school’ senior leadership culture or shaped by external forces such as regulation or supply chain dependencies.
There are low levels of knowledge and understanding of advanced technologies and lower general technology skills.
Businesses are risk averse and often see new technology as posing significant legal or reputational risks or posing a threat to the business.
These businesses have no dedicated budgets and have low skill resources.
Their market is quite steady and reliable, but their sector is not technology focused.
They are often not seeking significant growth.
These businesses are not interested in changing their structures and processes.

Their lack of interest and knowledge in new technology indicates very low levels of willingness, and these businesses have low capability due an absence of skills, knowledge and confidence around adopting new technologies. Capacity is also limited due to a lack of dedicated budgets/allocation of staff to work in these areas. Case study 10 in the Appendix illustrates the key findings for this business type.

Detached traditionalists

These tend to be older, smaller and specialised businesses where new technology does not play a key role.

There is a lack of buy in to the value of advanced technology across the business, mostly due to lack of awareness of new technologies and their potential benefits to the sector and business.
Advanced technology is not seen as core to the business mission, identity or offer, nor is it commonly used in the sub-sector.
Businesses are tolerant of risk when there is a clear business case and may be unaware of the risks associated with advanced technologies.
As smaller businesses, they have no dedicated budgets, and investment would likely need to be client driven or provided by investors or government.
These businesses are comfortable in their marketplace and seeking small manageable growth. As small businesses they regularly shift to deliver more bespoke services to clients.

In comparison to Tech Resistors, these businesses have slightly higher levels of willingness (although still low), as not considering advanced technologies is due to lack of awareness or not realising benefits rather than opposition. Their capability is low due to lacking specific skills. While capacity is low their business structure and risk appetite appears able to allow them to mobilise resources towards technology if it fit a clear client need. Case study 11 in the Appendix illustrates the key findings for this business type.

Question 5

5.  Conclusions: effective policy interventions to drive business uptake of advanced technologies

Accepted Answer

5.1 Introduction

This chapter sets out suggested interventions for each category of the Willingness, Capacity and Capability model and each of the typologies based on the research insight.

5.2 Summary of most effective intervention ideas

Businesses were asked to consider spontaneously what could help them to overcome key barriers to adoption and then shown stimulus representing a range of potential categories of government intervention (see Appendix 3). Most of the categories shown to participants were seen as potentially beneficial in encouraging adoption.

After seeing stimulus materials and engaging in further discussion, 4 leading types of intervention were identified by businesses. Of these, based on the strength of interview responses, forms of market interventions and financial incentives that would allow businesses to consider, experiment and invest in advanced technology were felt to be likely to be most effective.

Market Interventions (e.g. changing regulations and standards) shaping the market environment were a key area of government action highlighted, though views varied by sector and regulatory outlook. Key applications were in clarifying regulations (e.g. around AI and higher-risk sectors such as Finance), reducing regulatory barriers (e.g. in Manufacturing) and mandating forms of technology adoption.
Government-supported staff training was particularly valued by businesses facing uncertainty and skill shortages.
Providing information to raise awareness of technologies and their benefits was widely seen as important: if clear and accessible and credible, highlighting business benefits and aligned with a clear use case for adoption.
Financial Incentives (e.g., subsidies, grants, tax incentives ) were regarded as having potential to drive adoption, by impacting businesses’ cost-benefit calculation and addressing barriers related to limited resources and skills (particularly for SMEs). Businesses mentioned how incentives tied to specific technologies (e.g. AI), and indirect encouragement such as promoting quasi government agencies could help facilitate adoption.

Businesses felt the interventions discussed would be most impactful in combination , for example tailored information with training opportunities and a clear financial incentive, mentorship to put training into action and a range of market/innovation system/infrastructure interventions to increase confidence that technologies would work.

“You give people the skills and you give them the money and you give them a legal mandate and… it’s going to happen.”

(Creative industries, Small)

5.3 Suggestions for support and intervention to increase Willingness, Capacity and Capability

Before and after seeing the intervention categories suggested in the stimulus, businesses discussed specific suggestions for interventions. These can be mapped across the Willingness, Capability, and Capacity (WCC) model and are explored against each in turn below.

Table 5: Summary of interventions to help support adoption across the willingness, capability, and capacity model

Aspect of WCC	Interventions suggested by businesses
1. Willingness to consider a technology	Providing information to increase awareness of advanced technologies and their benefits; Helping businesses realise use cases; Promotion of knowledge sharing and best-practice; Market interventions to provide regulatory clarity
2. Capability to implement change	Financial incentives to address cost constraints; Staff training programmes to encourage adoption readiness; Support to improve business capabilities; Information or guidance to enable more confident decisions for those with high uncertainty/limited time; Harmonise and streamline regulation to remove specific barriers
3. Capacity to devote resources	Financial incentives to enable re-orientation towards advanced technology driving growth; Address resource-limiting aspects of environment and market; Tailored information to highlight capacity/growth building potential of technology

Interventions to increase Willingness to consider a technology

Many of the factors discussed influenced willingness to adopt (limited awareness, fear and lack of clarity of use case) and this was identified by businesses as a key area for government intervention and support.

After being shown prompts for potential interventions, the first way businesses felt the government could increase willingness to adopt was in providing information to raise awareness of advanced technologies in the UK.

Broadly, this was felt to help more traditional organisations and sectors recognise the need to move from outdated to newer technologies.
Businesses wanted information to be as tailored as possible to their sector, sub-sector, and size (particularly small businesses)^{[footnote 7]}, and to leadership and non-expert decision makers.
Trusted sources were key: these currently include industry experts, peer groups and regional and sectoral bodies. Businesses discussed avoiding overly ‘politicised’ government campaigns or sales-focused initiatives from suppliers.
Specific interventions mentioned included: a dedicated government organisation providing free, tailored advice on advanced technology, and support in forming or being directed to an organisational equivalent of the National Cyber Security council to provide board level guidance.
Businesses also highlighted the need for more confident statements of the government’s position on advanced technologies, particularly AI, to address cross-sector uncertainty. This was discussed mainly in relation to how safe advanced technologies are to use, with regulation as part of this - in terms of some businesses wanting to know how likely or unlikely they would be to receive a fine due to usage.

“If we knew how to use a lot of these technologies, we would be lot more on board with them. I think they frighten a lot of us, and a lot within the industry are of my age, that are scared of some of the new technologies.”

(Retail, Small)

The second effective intervention area highlighted by businesses was helping to realise potential use cases.

Businesses with limited experience of technology and little capital to risk mentioned interest in incentives for trialling through “try before you buy” schemes, or opportunities to rent technology at a limited cost or trial subscriptions.
- This was associated with AI, where identification of use cases lagged behind increasing awareness.
More technologically experienced businesses also responded positively to the idea of government promoting knowledge-sharing and best practice, for example through relevant use cases.
Across sectors, businesses wanted to understand divergent uses of technology by their peers and potentially share trialling and adoption costs, especially in competitive sectors like Finance.
- Appealing interventions included case studies (e.g. from large organisations presenting their adoption experiences), peer group support and collaborative testing (e.g. from the largest businesses within a sector).
- Promotion of business community forums was highlighted as an opportunity to reduce risks associated with overreliance on vendors.

“I think ultimately the whole industry would be in a much better place [if knowledge was shared], there would be a lot more respect, and there’d be a lot more innovation, and a lot more efficiencies being produced.”

(Manufacturing, Medium)

Thirdly, some businesses were most concerned with their risk appetite. Here, market interventions producing a clearer regulatory framework were desirable.

This was a particular constraint on business decisions in sectors with high levels of risk and/or regulation such as Finance and Manufacturing, and around AI.
Key sector differences were evident: Finance businesses sought clearer regulatory guidelines, including specific answers to ambiguities whereas Manufacturing organisations appeared more likely to request that government sought to streamline regulation in line with other global frameworks.

Interventions to increase Capability to implement change.

Limitations in capability were often cited by businesses who, as outlined previously, perceived cost as the greatest constraint on decisions. Financial incentives were felt to be most effective in addressing this.

These were felt to allow businesses to build the necessary dedicated resource to explore and build confidence in implementing new technology, in terms of sufficient time, staff, and skills. This was particularly valued by SMEs willing to consider technologies, but with insufficient resources to do so.
Interventions to help increase this resources included government grants focused on purchase of advanced technology, business size- and sector-specific forms of tax relief and subsidised funding plans tailored to start-ups needs.

“The government [should be] making a contribution to all to businesses to advance their technology because at the moment all technology is expensive.”

(Creative industries, Small)

Those in larger businesses discussed the need for interventions to encourage their staff’s adoption readiness, both in terms of confidence and expertise.

Businesses responded positively to the idea of staff training programmes, especially if these could also be incentivised, for example through tax savings to offset adoption costs.

Some businesses that had been slower to innovate believed the support provided to improve business capabilities during the UK Covid-19 pandemic (e.g. around promoting remote working tools) could be emulated in promoting advanced technology.

These interventions, including a combination of financial support, regulatory guidance, and digital enablement initiatives were felt to gradually enhance capability at a market level.

Businesses also identified a set of information- and guidance-related interventions to support their limited resources and reduce uncertainty.

Interventions could help overcome time constraints in reviewing technologies, and reluctance to engage with untrustworthy or self-promoting vendors. Businesses drew comparisons to the guidance and expertise valued in the green technology sector.
Key interventions felt to achieve this were guidance on credible providers and intermediaries such as through government-backed lists of approved suppliers/advisors (especially in ‘problem’ areas), or a verification portal and providing access to impartial advisors and mentors through dedicated government advisors or mentors, such as export advisors.
Throughout, businesses emphasised how the quality of the product/service and advice would have to be clear for them to commit their time.

Smaller, time-poor businesses with limited resource appeared to place more value on receiving easy and quick to digest information.

These included bite-sized ‘advice sheets’ tailored for advanced technology to different sectors, short videos that could be watched in a lunch hour and easily navigable government portals.
These needed to be designed for a non-specialist audience of decision makers outside of more “plugged in” roles such as those in IT and compliance.

“It’s not the lack of knowledge, it really is the lack of time.”

(Professional services, Small)

Certain businesses (especially in Finance, Manufacturing and Retail), responding to stimulus around market interventions, identified opportunities for government to harmonise and streamline regulation to remove specific barriers to implementing change with the resources they had.

For some global businesses, market interventions were felt to be needed to harmonise regulations between markets post-EU Exit.
Other businesses were focused on barriers to implementing specific technologies. For example, one large retail business said UK drone testing rules delayed expanding delivery range beyond 2 miles for 11 years, which they found frustrating.

Finally, while not presented as a potential intervention, businesses spontaneously raised the importance of developing knowledge and expertise in advanced technologies in the UK through continuous changes and improvements to the education system.

“Continue to invest in an education pipeline that turns out people actually capable of driving technology adoption.”

(Retail, Large)

Interventions to increase Capacity to devote resources

As with Capability-related constraints, businesses reflected on perceived limitations in devoting existing resources to advanced technology.

A range of financial incentives were said to offer value in supporting re-orientation towards advanced technology.

Suggestions here included a system of loans where repayment was tied to a business achieving specific milestones and bursary-style system where the government would pay a percentage of set up costs for those adopting new technologies.

“[Government] should help grow a company into a large taxpayer… feed them with support and grants a bit like a student loan, that when you get to a certain point you have to start repaying the loan.”

(Manufacturing, Small)

More broadly, businesses valued interventions that in combination could address what were seen to be resource-limiting aspects of the environment or market.

For businesses looking to expand technology usage and those in remote areas in the UK such as northern Scotland, improvements to infrastructure like broadband were seen as key to overcoming capacity limits and driving confidence in new technology potential.

“In Aberdeen, despite us being the oil capital of Europe, the internet is very poor!”

(Manufacturing, Small)

Innovative businesses suggested interventions to helping create a better funding environment. For example, a Pioneer business in the technology sector encouraged the government to target this through industry-specific investment initiatives (e.g. sector-focused growth funds and R&D tax credits) in the UK to promote growth, making it easier to businesses to access funds to adopt advanced technology.
Other businesses described the need for the removal of counter-productive areas of compliance that had discouraged them from adopting advanced technologies, for example those that limited their more innovative environmental initiatives by setting overly specific criteria.
Advanced Market Commitments (a government committing to purchasing a set amount of a product once it is developed ) also appealed to some more innovative businesses in Finance and Professional services as a way to reduce opportunity costs, increase confidence and encourage investment in technology.
Similarly, businesses across sectors discussed the benefit of government support in creating centres of excellence, that would help make the UK more attractive by developing onshore capacity in terms of skills and innovation that they could then draw from.

Finally, businesses focused on information that would highlight the capacity/growth building potential of new technologies. One suggestion was to promote this through government-led events that harnessed the expertise of businesses, focused on demonstrating the cost-effectiveness and high margin of new technologies.

“If you’re trying to increase [adoption] the best way is to let people know that these don’t just make your life more efficient from a business perspective. They’re presenting you opportunities in which to actually get the revenue in because you can do things in a totally different way.”

(Professional services, Small)

5.4 Suggestions for how to support each business segment

The typology identified business segments with varied contexts, perspectives and needs. These segments could benefit from a targeted, distinguishing approach to tech adoption.

Pioneers

These businesses had fewer barriers to adopting advanced technology and higher levels of awareness, strategical alignment, leadership endorsement and the presence of expert internal teams. They tended to be more sceptical of government information and support as too generalist to meet their needs. Key challenges they faced related to technology adoption were constraints around resourcing and cost, and investment and surviving in competitive markets. Research suggests these businesses would respond to:

A combination of tailored financial incentives to help smaller businesses get resource in place, and highly tailored information from verified suppliers, experts and other experienced organisations .
Access to exclusive information to develop a business case for investors, to support growth and maintain a competitive edge.

Other types would also likely appreciate case study examples from Pioneer to demonstrate successful adoption processes.

Strategic adopters

These organisations were varied in their views on the scope of government support in technology adoption. Generally, they felt they could be supported by government actions to increase skills in the market, inspire market and consumer confidence, and interventions to improve the business environment. Research suggests these businesses would respond to:

Training to drive adoption readiness throughout their organisations
Reducing siloed knowledge and expertise, for example through peer group support or collaborative testing initiatives.
Collaborative testing to draw on collective expertise and skills to evaluate and identify advanced technology use cases .

Pragmatic followers

Given their more passive approach to innovation, the pragmatic follower group appears likely benefit from being able to identify use cases addressing specific business needs . Research indicates these businesses would respond best to:

Clear examples of applications to support their business’s strategic ambitions, for example case studies from other businesses, opportunities to trial and test advanced technology in a collaborative context, and focused peer group support initiatives to make the uses of technology real.

Reluctant adopters

Like pragmatic followers, these businesses typically struggled with identifying use cases for advanced technology but also more limited awareness and lack of strategic orientation. Research indicates they could be supported to become informed and less risk averse through:

Initiatives to increased the credibility of advanced technology such as government-backed initiatives, informative websites and case studies from older or more traditional businesses who had adopted in the past.
Other interventions to close the gap between existing knowledge and skills and that required for implementation such as funded training, mentor schemes and apprenticeships .

Technology resistors

These businesses did not see advanced technology as relevant solutions to their challenges and will be slow to adopt until the market conditions create strong pull factors to do so. Therefore, research indicates the most effective interventions for them would be:

Directly encourage or necessitate the adoption of advanced technology: such as tax incentives and new regulatory requirements.

Detached traditionalists

This segment’s lack of buy in to the value of advanced technology was generally shaped by sector norms and limited resources and interest in investing. Research indicates they could be supported through:

Sector-focused awareness-raising initiatives to make benefits more evident and trust-building initiatives (for example through pre-approved suppliers, and access to advisors and mentors) to reduce fear and the sense of risk in investing in newly advanced technology.

5.5 Putting the findings into action

This report has outlined the range of factors that drive business decisions around the adoption of advanced technologies and discussed the ways in which these inter-relate and influence business willingness, capability and capacity to adopt. It has also explored what were perceived to be the most effective combinations of intervention and support from government to increase uptake across the business population.

This report builds on a substantial existing evidence-base and is intended for a range of users across government and other organisations working on increasing advanced technology uptake. The rich qualitative insight into how business decisions are influenced by their business characteristics can be used to supplement quantitative trend data to inform DSIT and cross-departmental development of policy, as well as specific interventions to address the greatest barriers of particular segments.

Question 6

Appendix

Accepted Answer

Appendix 1: Full research Design

Background

The UK has witnessed poor labour and total factor productivity (TFP) growth since the 2008 financial crisis. There is now significant interest in increasing the adoption of advanced technologies, like Artificial Intelligence, due to their potential for driving higher productivity growth.

A deeper, more nuanced understanding is needed to explore how and why barriers and enablers prevent or facilitate technology adoption across the UK business population. Qualitative work is needed to explore in particular how businesses weigh up and negotiate these as well as the relationships and inter-connectedness between these factors. Insights from this work will contribute to the DCMS/DSIT evidence base on drivers of advanced technology adoption in businesses.

Members of the Innovation and Research Caucus (IRC) have explored existing evidence about drivers of low digital adoption among businesses and identified key aspects of demand and supply side dynamics and noted that adoption is primarily driven by business growth and specific needs^{[footnote 8]}. Members of the IRC at the University of Warwick conducted a literature review for this project involving 40 documents, which consolidated relevant literature in this area, adding to the evidence base for the study. The literature review highlighted the relevance of the Technology-Organisation-Environment Framework (TOE) to adoption decisions^{[footnote 9]}. The TOE framework identifies 3 main categories of factors influencing business adoption decisions: factors relating to the nature and characteristics of the technology itself; factors related to the structure and characteristics of the organisation; and factors related to the wider external sector and societal context (or surrounding environment in which the organisation is operating). This framework was used to help structure the discussions with businesses in this research.

Aims

The aims of this qualitative research are to:

Further our understanding of the drivers of business decisions around adoption of new emerging / advanced technologies
Further our understanding of how businesses are experiencing barriers and enablers to adoption and diffusion in more depth, including how these differ according to business characteristics

The specific research questions are:

What are the specific and tangible barriers to technology adoption that businesses across the chosen sectors perceive that they face?
- Which barriers are seen as the most significant? Are barriers internal or external to the business?
What are the specific and tangible enablers to technology adoption that businesses across the chosen sectors perceive to support adoption?
- Which enablers are seen as the most important?
Are barriers and enablers to technology adoption specific to individual sectors or are there commonalities?
- How do barriers and enablers vary by business characteristics such as business size, the type of tech, etc
- Are there ‘segments’ of businesses within the economy who tend to experience barriers and enablers in particular ways, with common characteristics such as business strategy, size etc?
What government interventions do businesses need and want to address barriers to technology adoption and why?

Scope

The primary focus of this research is to explore the main enablers and barriers to adoption of advanced technologies for UK businesses. We note that ‘advanced technologies’ is a broad term encompassing numerous and highly diverse technologies and different use cases (including customer facing and back-office applications) and that there is no universally accepted definition of ‘advanced technology’ partly due to the pace of technological change and range of opinions available. A working definition was agreed during the scoping phase of this project through the literature review as:

Cutting-edge technologies at the boundaries of existing scientific, engineering and technological knowledge which are likely to integrate elements from domains such as digital technology, data science and analytics, AI, robotics and material science.^{[footnote 1]}

The scope of advanced technologies included for discussion in this research was limited and contained within 4 technology ‘clusters’, derived from DSIT’s Innovation Diffusion and Adoption (IDA) Survey^{[footnote 10]}. They are listed below and the full description of them used in the research is included in Appendix 2.

Cluster 1: Information and communication technologies
Cluster 2: Advanced computing technologies
Cluster 3: Advanced Manufacturing and Materials
Cluster 4: Energy and Environmental Technologies

DSIT/DCMS evidence suggests that the diffusion of new and emerging technologies contributes to stronger labour productivity growth in the wider economy. This research is primarily interested in the drivers of advanced technology adoption decisions, rather than what businesses do to improve business-level productivity or growth specifically. Businesses discussed barriers and enablers to adoption of technologies for a range of reasons in addition to growth.

While this research focuses on business adoption decisions, it is important to recognise that technology adoption is not a one-off decision but a journey with several phases. While the study does not focus on experiences of technology integration it considered businesses’ assumptions and perceptions about implementation insofar as they affect adoption decisions.

Methodology

The design for this research was iterative, incorporating 2 phases, with collaborative reviews between each phase to refine and refocus as needed.

Project set up and scoping phase

This phase involved a literature review and a stakeholder workshop. This phase ran from December 2024 until the start of the recruitment period in January 2025.

Following kick off workshops, IRC academics from the University of Warwick conducted a systematic review, searching academic databases and grey literature of 40 articles – guided by a literature protocol agreed with DSIT – to identify evidence about barriers and enablers to UK business technology adoption. Findings from this review informed the design of the primary research.

Verian led a 2-hour online workshop with government stakeholders and IRC partners to reflect on the findings from the literature review and agree the final design of the primary research. The key aspects of the approach agreed at this stage were on the definition of advanced technology to use in the research, the clusters and technologies to use in research, and in the application of the TOE framework to discussions with businesses.

Primary research

This study took a qualitative approach in recognition that the complex dynamics and perceptions shaping business adoption decisions cannot be sufficiently understood through quantitative data alone. Qualitative interviews explored how individual business contexts and perspectives inform their decision making and experiences. In particular, this approach sought to get beyond surface-level explanations of technology adoption (such as “cost” or “skills” as high-level barriers to adoption) and capture variations in views and experiences across business contexts, sectors, and technology clusters.

The method used was one-hour semi-structured interviews, conducted online through MS Teams using a semi-structured interview guide of key questions and follow up prompts and probes. The fieldwork for this project took place from 17 January to 6 March 2025. The sample consisted of 80 business interviews, of which 8 were deep-dive case studies with 2 participants designed to gather multiple perspectives on decision making within a business. Businesses were given the option of taking part in the case study individually or as a paired depth.

To supplement this insight with a more holistic perspective on sector-specific and system-wide barrier and enablers, 8 stakeholder interviews were conducted with those who had varied roles in facilitating adoption of advanced technology, such as consultants, trade associations and technology providers. More detail on sampling is below and in Appendix 4.

Participants were identified and invited to take part through free-find recruitment techniques. All participants completed a screening questionnaire to establish eligibility. A snowballing technique was used to recruit the cases studies from the primary contact. All participants were offered a £100 voucher or charity donation as a token of appreciation for their time.

The businesses interviewed were divided into 2 groups, businesses and stakeholders. The key recruitment variables are outlined below and a full achieved sample frame is in Appendix 4. The key eligibility criterion for the 80 business interviews was for individuals to be decision makers or those with knowledge of the decision-making process for advanced technology adoption in their business. 3 primary quotas were set for this research audience, each corresponding with characteristics expected to inform barriers and enablers: sector, business size, and level of technology adoption. 5 sectors were included in this research: Manufacturing, Retail, Finance, Creative industries, and Professional, Scientific and Technological Services. These were selected to provide breadth to the research. Size of business was defined by number of employees, including small/micro (1-49), medium (50-249) and large businesses (250+). Level of technology adoption was based on whether businesses reported adopting technology before or after others in their sector. A minimum of 3 participants were recruited against each variable in the quotas across all 5 sectors.

Secondary variables were included to achieve a spread of relevant business demographics hypothesised to shape decision making, namely: age of business, region, turnover, ownership, whether a business was part of a group, and exporting status. Recruitment also captured whether businesses had adopted, were considering, or not considering adopting any of the advanced technologies across the 5 technology clusters.

The 8 stakeholder interviews included a range of participants with expertise either in specific advanced technologies of interest, or technology adoption within the 5 sectors included in this research; i.e. sector / industry / trade bodies, Consultant / advisor / business service businesses, Innovation hubs / universities, Government / public sector agencies – helping businesses adopt advanced technologies, and Technology provider (of advanced technologies).

Analytical approach

Given the volume of rich detailed qualitative data produced, and need to manage the data systematically and rigorously, a framework approach to analysis was undertaken. A framework was developed which mapped the data for each case against the research objectives and the TOE Framework. Following this data management phase, key themes were identified through the use of creative brainstorming sessions. These key themes were validated, refined and iterated through immersion in the data. Sub-group variation was identified through use of sorting of the cases in the framework.

The thematic analysis was supplemented with the creation of a typology to identify distinct business segments across the sample. By focusing on likelihood to adopt, the typology helps to understand variation in experiences of advanced technology adoption across the sample and crucially what different forms of government support will be most appropriate to different groups. The typology was developed through a combination of exploring the framework and discussion during analysis sessions about variation in likelihood to adopt. The segments were hypothesised and then validated against each case in the framework and refined.

Appendix 2: Full list of technologies includes in clusters

Cluster 1: Information and communication technologies

Artificial Intelligence (AI) (including, but not limited to, Machine Learning)
Future Computing & Data Management Technology (including, but not limited to, Future Computing Paradigms, Big Data Infrastructure, Privacy Enhancing Technology)
Extended Reality, Immersive and Synthetic Environment Technologies (including, but not limited to, Augmented Reality (AR), Virtual Reality (VR), Digital Twins)
Future telecoms (including, but not limited to, 5G/6G, Wireless Communications, Cloud Communications, Satellite Communications)

Cluster 2: Advanced computing technologies

Robotics, Drones and Autonomous Systems
Quantum Technology (including, but not limited to, Sensing and Metrology)
Photonics and non-Quantum Sensors (including, but not limited to Light Detection and Ranging (LIDAR), Radio Detection and Ranging (RADAR), Quantum Photonics, Biophotonics)

Cluster 3: Advanced Manufacturing and Materials

Manufacturing technologies including additive manufacturing (including, but not limited to, 3D, 4D printing)
Advanced Materials (including, but not limited to, Novel or Complex Metal Alloys, Advanced Composites, Engineering and Technical Polymers and Ceramics)
Novel Electronics and Position, Navigation and Timing Technology (including, but not limited to, Flexible Electronics, Printed Electronics)

Cluster 4: Energy and Environmental Technologies

Low Carbon Energy, Heating and Propulsion Technologies (including, but not limited to, Nuclear, Renewables)
Recycling and waste technology (including, but not limited to, Carbon Capture, Usage and Storage (CC(U)S))
Battery and energy storage technologies

Appendix 3: List of possible interventions shown to businesses in the interviews

Market interventions (e.g. changing regulations and standards
Improving UK infrastructure (e.g. broadband access)
Providing information to raise awareness of the benefits of advanced technologies (e.g. benchmarking information)
Staff training
Support to improve business capabilities (e.g. access to students/apprentices with skills and knowledge)
Advanced Market Commitments (a guarantee there will be some purchases of products developed using the new technology)
Campaigns or policies to promote an entrepreneurial culture, improved management practices and/or long-term investment strategies
Financial incentives (e.g. subsidies, grants, tax incentives)
Campaigns to encourage uptake
Peer group support (e.g. networks) Access to advisors and mentors
Changes to UK innovation system
Collaborative testing of new technologies

Appendix 4: Achieved sample

Sample for business interviews

Table 1: Total

TYPE	TARGET	COMPLETED
Depths	80	80
Case Studies	10 to 15	8

Table 2: Business primary quotas

SECTOR	TARGET	Manufacturing COMPLETED	Retail COMPLETED	Finance COMPLETED	Creative COMPLETED	Professional, scientific and technical COMPLETED
Sector total	Min 14	16	15	17	17	16
Business size (no. of employees)
Small / micro (1-49)	min 4	5	5	6	8	6
Medium (50-249)	min 4	5	5	6	4	5
Large (250+)	min 4	6	5	5	4	5
Level of tech adoption
Laggard / late majority	min 4	4	4	5	3	6
Early majority / adopters	min 4	4	4	8	4	6
Innovators	min 4	8	7	4	10	4

Table 3: Business secondary quotas

Breakdown	TARGET	COMPLETED
Age	Mix and monitor across whole sample
Startups (0-3 years)		4
Established (4-10 years)		19
Long-standing (10+ years)		58
Region	Ensure spread across all 12 regions (including Scotland, Wales, NI)
East Midlands		6
East of England		3
London		25
North East		0
North West		6
Northern Ireland		1
Scotland		10
South East		17
South West		2
Wales		2
West Midlands		5
Yorkshire & The Humber		4
Turnover	Mix and monitor
small (<£10.2m)		43
medium (up to £36m)		17
large (>£36m)		20
Ownership	Mix and monitor
Private limited company (Ltd)		69
Public limited company		7
Partnership		3
Other		1
Group	Monitor
Business is part of a group		29
Export status	Monitor
Currently exporting		39
Have exported in the past		6
Never exported		36

Table 4: Business cluster breakdowns

Adoption of tech clusters	TARGET	Has adopted one or more of the advanced technologies COMPLETED	Is currently in the process of adopting or actively considering adopting 1 or more COMPLETED	May start considering adopting one or more in the next year COMPLETED	Not currently considering adopting one or more and unlikely to do so in next year COMPLETED
Cluster 1: Information and communication technologies	Monitor	50	15	12	5
Cluster 2: Advanced computing technologies	Monitor	17	12	20	29
Cluster 3: Advanced Manufacturing and Materials	Monitor	16	7	17	37
Cluster 4: Energy and Environmental Technologies	Monitor	27	12	14	26
Cluster 5: Life Sciences and Healthcare technologies	Monitor	10	4	7	51
Any other types of advanced technologies	Monitor	11	5

Table 5: Business technology breakdowns

Technology	TARGET	Has adopted COMPLETED
Cluster 1: Information and communication technologies	Monitor
Artificial Intelligence (AI)		55
Future Computing & Data Management Technology		30
Extended Reality, Immersive and Synthetic Environment Technologies		12
Future telecoms		20
Cluster 2: Advanced computing technologies	Monitor
Robotics, Drones and Autonomous Systems		28
Quantum Technology		0
Photonics and non-Quantum Sensors		0
Radio Detection and Ranging (RADAR), Quantum Photonics, Biophotonics		0
Cluster 3: Advanced Manufacturing and Materials	Monitor
Manufacturing technologies including additive manufacturing		17
Advanced Materials		0
Novel Electronics and Position, Navigation and Timing Technology		0
Cluster 4: Energy and Environmental Technologies	Monitor
Low Carbon Energy, Heating and Propulsion Technologies		27
Recycling and waste technology		28
Battery and energy storage technologies		10
Cluster 5: Life Sciences and Healthcare	Monitor
Medical technologies		8
Biotechnologies		4

Sample frame for stakeholder interviews

Table 6: Stakeholder total

TYPE	TARGET	RECRUITED
Depths	8	8

Table 7: Stakeholder sector quotas

SECTOR	TARGET	Manufacturing COMPLETED	Retail COMPLETED	Finance COMPLETED	Creative COMPLETED	Professional, scientific and tech COMPLETED
Sector total (multi-coded)	mix	4	2	2	1	7

Table 8: Stakeholder additional quotas

BREAKDOWN	TARGET	COMPLETED
Stakeholder type	Mix
Sector / industry / trade bodies or professional associations –has knowledge of new technology adoption in their sector		2
Consultant / advisor / business service business – helping businesses adopt advanced technologies		2
Innovation hubs / universities – specialising in business adoption of the advanced technologies		1
Peer networks – with a role including working on or supporting advanced technology adoption		0
Government / public sector agencies – helping businesses adopt advanced technologies		1
Technology provider – meaning relevant advanced technology developer/ producer /manufacturer or software developer or seller of advanced technologies		2
Cluster 1: Information and communication technologies	Record
Artificial Intelligence (AI)		6
Future Computing & Data Management Technology		3
Extended Reality, Immersive and Synthetic Environment Technologies		0
Future telecoms		0
Cluster 2: Advanced computing technologies	Record
Robotics, Drones and Autonomous Systems		2
Quantum Technology		0
Photonics and non-Quantum Sensors		0
Radio Detection and Ranging (RADAR), Quantum Photonics, Biophotonics		0
Cluster 3: Advanced Manufacturing and Materials	Record
Manufacturing technologies including additive manufacturing		3
Advanced Materials		0
Novel Electronics and Position, Navigation and Timing Technology		0

Alignment of the factors with the Willingness, Capability and Capacity model

Table 9: Technology-Organisation-Environment and Willingness, Capability, Capacity Model Alignment

TOE Level	Factor	Willingness	Capability	Capacity
Technology level factors	Clarity and relevance of use case	Whether the business understands the benefits and sees the technology as relevant to them
	Technology risk	Perceptions of reliability of functionality
	System alignment	Perceptions of alignment with existing systems		Practical aspects of integrating with existing systems can challenge capacity
	Perceptions of usability	How user friendly a technology is seen to be
Organisation level factors	Affordability		Whether a business has the resources necessary for purchase, integration and maintenance	Whether resources can be deployed for this purpose at this time
	Access to skills		Whether the business has access to the skills necessary to implement and use the technology	Whether the skills are available and can they be deployed to integration and use at this time
	Business risk profile	Shapes whether business is likely to seek technology based solutions and the extent to which they are prepared to accept risks and uncertainties		Shapes the degree to which business is willing to direct resources to integration
	Leadership attitudes	Shape whether the business is likely to seek technology based solutions as they drive direction and priorities		Leaders decide how to allocate resource
	Strategy / strategic ambitions	Degree of alignment with strategic ambitions		Strategy dictates what is prioritised for resourcing
	Brand values	Alignment with brand values
	Employee attitudes	Degree to which employees are seen to welcome and engage with technology changes		Degree to which employees are perceived to facilitate or oppose technology integration
	Presence of business structures	Internal structures can encourage or discourage seeking technology solutions	Internal structures can be set up for agility and change management or mean that adoption requires large internal structural adjustments
External level factors	Standards and regulations	Concern about meeting regulatory requirements can either encourage or discourage specific technology pathways		Resource needs to meet regulatory requirements affect capacity
	Customer dynamics	Demand from customers can encourage adoption of specific technologies		Extent to which customers are prepared to pay for use of new technologies
	Supply chain dynamics	Requirements in the supply chain can encourage or discourage adoption	Passive upgrading can change business access to technologies
	Competitor dynamics	What competitors are doing can drive businesses to consider technology they might not otherwise have to avoid falling behind		The need to keep up with competition can encourage allocation and resources to avoid falling behind
	Sector norms	Standard ways of operating in the sector can mean that businesses are generally more or less open in some industries than others to considering tech solutions
	Investor pressure	Investors can encourage businesses to consider tech solutions		Investors may provide funding for adoption
	Access to trusted advice	Trusted advisors can affect business confidence and encourage or discourage them to consider technology solutions	Trusted advisors can offer knowledge and skills to increase capabilities

Appendix 6: Case studies

Case Study 1: Manufacturing

Manufacturer of print magazines

Sector: Manufacturing
Size: Medium
Typology: Reluctant adopter

Interested in: Robotics, renewable energy, recycling and waste technology.

Background: Established manufacturer of print magazines and specialist publications. Currently navigating decline of the print sector and trying to survive as a business. They think that automation will be key to their survival as a business.

Key factors that drive adoption of advanced technology: clarity of use case and value to the business, affordability, sector norms.

This business acknowledges a range of ways that advanced technologies could positively impact their business, including waste management technologies to address the extent of waste that they produce and robotics to make their printing process more efficient.

The use case for robots is the main catalyst for them – robots are faster, more accurate and could work for longer hours than humans. However, cost acts as a constraint. Robots are expensive, and they would have to trade off the cost of machinery against the cost of wages. Concerns about operational disruption are also a constraint, with the introduction of new technology needing to align with their manufacturing cycles (including their press replacement cycles and their regular print cycles).

In addition, sector norms act as a barrier to adoption as there is a sense that there is minimal pressure from competitors to innovate and employees can be reluctant to change the ways in which they work and learn to use new technologies, especially when advanced technology is perceived as potentially replacing their jobs.

It’s purely cost…we would do it now otherwise, because there’s not much of an argument to suggest you wouldn’t.

If I believe it will win more work and add value…that would conquer most other arguments, as long as it’s not totally disruptive within the business, because ultimately, without the sales, we will not survive.

Case Study 2: Retail

Grocery retailer

Sector: Retail
Size: Large
Typology: Strategic adopter

Interested in: AI and big data, low carbon energy, and robotics.

Background: Multinational grocery retailer with a continuous innovation pipeline that evaluates the suitability of technologies that can disrupt the retail industry, including in the energy and robotics areas.

Key factors that drive adoption of advanced technology: clarity of use case and value to the business, affordability, access to skills, strategic ambitions, attitudes towards innovation, competitor dynamics.

Although innovation is highly important to this business, due to the scale of their operations, technology needs to have reached a certain level of maturity before they can implement it. Despite this, they claim they aim to disrupt the market and consideration, and development of advanced technology is one of their strategic goals. Both leaders and employees are open to technological innovation. Budget isn’t seen to be a strong limiting factor for this business; however, technology will require a clear use. This business is particularly interested in robotics to automate picking systems either for customer fulfilment or distribution. This addresses the issue of reported labour shortages and makes their operations more efficient in the context of pressure to maintain and improve productivity levels.

Cost and return on investment are ultimately the most important factors driving their decision despite some concerns about the impact that advanced technology could have on their employees.

We’re always looking at ways in which we can reduce our reliance upon labour because labour is actually in quite short supply in the UK.

Case study 3: Finance

Insurance company

Sector: Finance
Size: Small
Typology: Pragmatic follower

Interested in: Data management, AI, and future telecoms.

Background: Insurance company specialising in medical and professional indemnity insurance. They are regulated by the Financial Conduct Authority.

Key factors that drive adoption of advanced technology: clarity of use case, systems alignment, affordability, standards and regulation.

Growth and innovation are important to this insurance company, and they are interested in technology that allows them to work faster and process data quicker which ultimately saves them time and money. The technologies in Cluster 1 are therefore most relevant to this business.

However, this business doesn’t want the pursuit of growth to mean that they compromise on adhering to regulations. Any technology that they introduce must comply with FCA regulations. Particularly in relation to AI, they feel that guidance is lacking and this affects their confidence to adopt.

Alignment with their current systems is also important and they want to ensure that any new technology can integrate with their current systems.

We will always look into things and try things out, but we will always try and make sure that there’s some review work done ahead of making that investment.

There needs to be rules around how you can and cannot use AI as a regulated business.

Case study 4: Professional services

Management consultancy

Sector: Professional services
Size: Small
Typology: Pioneer

Interested in: AI, Future computing and data management, Extended reality, Future telecoms

Background: IT Management consultancy and app developers that provide services to the financial services sector. They are a small and agile business which they believe gives them the flexibility to adopt new technology.

Key factors that drive adoption of advanced technology: value of technology, affordability, access to skills, attitudes to innovation, standards and regulation.

Innovative and agile, this business is bought in to the benefits of advanced technology and wants to retain its position as a market leader. They have already adopted a range of technologies across Cluster 1 including AI and machine learning.

Technology that will lead to growth is the most important catalyst to adoption and in deciding whether a certain technology covers what they need, they will consider whether it will increase sales and what the opportunity costs are of adopting or not adopting.

Regulatory uncertainty is a constraint to adoption as they don’t always have guidance on new and innovative products and have concerns about working on adopting a new product that is subsequently disallowed by regulators.

Whether the business has the skills and expertise to adopt advanced technologies is also an important consideration. When adopting AI, they had to weigh up whether they should retrain existing staff or whether they needed to bring in an external expert and when they did find expertise in LLM technology, the cost was too high. The benefit of the technology would have to be significant to justify the cost.

We’re almost hungry for new technologies and really keen to adopt new technologies. So really the decision-making process is price and if we can afford it, we’ll try and go for it.

Sometimes when you’re as innovative as us…we’re ahead of the markets. We’re ahead of…case studies of what’s right, what’s wrong, what the regulator might come in [and say].

Case study 5: Creative industries

Children’s entertainment company

Background: Global entertainment company that creates and distributes video and audio content. They want to be industry leaders in children’s entertainment and are always experimenting with new technology.

Key factors that drive adoption of advanced technology: Technology risks, systems alignment, strategic ambitions, attitudes towards innovation among leaders and employees, standards and regulation.

As a result of their ambitions to be industry leaders, this business is open to experimenting and taking risks with new technologies. They believe that advanced technology can make them more efficient by automating certain tasks which allow their team to focus on more creative and strategic work. They also recognise that advanced technology will enable them to make data led decisions that drive revenue.

It is also important for them that any new technology fits in with their existing technology stack.

However, they have significant concerns about copyright – they do not want to risk being sued. They are also worried about how their use of AI might be perceived by customers, feeling that using AI too much for creative work is controversial. As a result, they are being deliberately purposeful with how they use advanced technology and try not to let it creep into their creative work.

If the people making these technologies aren’t inherently being asked to consider copyright concerns, then it falls on the businesses to have to consider that, and then that is just another barrier stopping us from being able to adopt a technology that could be really helpful

Case study 6: Pioneer

Online events planning platform

Sector: Creative industries
Size: Medium
Typology: Pioneer

Interested in: AI and machine learning, big data, recycling and waste technology, and VR. Background: Start up business that provides a marketplace platform that connects event suppliers with event organisers. Currently on an aggressive growth journey aiming to expand their customer base and supply into larger events. They pitch themselves as an innovative technology business that takes a data led approach to how they work.

Key factors that drive adoption of advanced technology: use case, affordability, leadership attitudes, strategic ambitions, alignment with brand values, attitudes to innovation among leaders and employees, investor pressure, competitor dynamics.

This business and its leaders are bought into the value of advanced technology – it is core to what their business does and the technology that they use is what differentiates them in the market. They have already adopted tools that maximise efficiencies and allow them to do more with the data they have, for example, they have a matchmaking tool on their platform that uses AI to find the best suppliers for customers and have generative Chatbots that interact with users. This technology frees up staff time for other tasks.

It is important to them to be early adopters of advanced technology as it demonstrates that they are at the cutting edge of the technology frontier. They think that this is beneficial for the positioning of the business externally and attracts top talent.

Although they have privacy concerns about AI, this doesn’t stop them from using it. They want to own the narrative around AI in their sector to ensure that they aren’t replaced by it. The main barrier to adoption that they have experienced is having the skills internally to integrate new technology with their existing systems. Therefore, staff skills and bandwidth are the most important constraints to adoption – they are confident that if they can prove the business case, they will get the finance.

Our whole thing is about having this cutting-edge technology in the events space.

The first series of companies to employ AI effectively in this space will win. . You’re making an investment in time, cost and opportunity basically.

Case study 7: Strategic adopter

Luxury cosmetics retailer

Sector: Retail
Size: Large
Typology: Strategic adopter

Interested in: AI, Future telecoms and the Metaverse, Low carbon manufacturing.

Background: Cosmetics retailer part of a global group known for its luxury cosmetics and sustainable practices. They have a formal process for adoption of advanced technology and have dedicated budgets for innovation.

Key factors that drive adoption of advanced technology: clarity of use case and value, leadership attitudes, strategy, alignment with brand values, customer dynamics.

Technological innovation is important to this business, with both leaders and employees bought in to the value of advanced technology and the culture of innovating. Introducing advanced technology is part of their strategy and they also encourage individual employees to submit innovative ideas for consideration.

Their customers are central to their decisions, so any new technology needs to deliver value to their customers. Any advanced technology that this business adopts needs to align with their brand and they are conscious of their reputation. They don’t want to risk damaging their reputation by using certain technologies before they have carefully considered the legal and ethical implications. As a result, they have a rigorous process for testing new technologies and described themselves as taking a measured approach.

We’re very much focused on progress and the future and embracing new technology, but [we] also have that level of balance, in that [we] won’t do anything that may damage our reputation.

Case study 8: Pragmatic follower

Manufacturer of bar and cellar equipment

Sector: Manufacturing
Size: Small
Typology: Pragmatic followers

Interested in: AI, Advanced materials, recycling and waste management Background: Established, family run manufacturer of bar and cellar equipment. They are operating in the context of a declining market but plan to maintain the business and to expand their product range.

Key factors that drive adoption of advanced technology: clarity of use case and value, affordability, leadership attitudes, competitor and customer dynamics, access to trusted advice.

With previous experience of adopting advanced technology, including AI and 3D printing, this business is open to innovation and technological advancements. Innovating is seen as a way to remain competitive.

For this business to consider an advanced technology, a clear and specific use case is needed. For example, they adopted AI to improve productivity as it could save time spent researching - this has enabled them to try and grow the business without increasing costs. Similarly, 3D printing offered a cost-effective solution to producing and testing prototype manufacturing machine parts.

Customer demand is often a key enabler for this business with requests to trial new materials triggering them to consider advanced materials or alternative technologies.

Access to trusted advice has also been a key enabler for this business as they forged a Knowledge Transfer Partnership with a local university which involved the university stress testing different materials for one of their products and also giving them their advice on potential materials. This partnership and unbiased advice gave them the reassurance that they needed to adopt certain advanced technologies.

The way you win in business is by being innovative.

It [3D printing] gave you that reassurance of yes, this is going to produce XY which can then be tested in an environment that’s controlled before moving it on to a major tooling or production.

Case study 9: Reluctant adopter

Law firm

Sector: Professional services
Size: Medium
Typology: Reluctant adopter

Interested in: AI, Future computing, Future telecoms and Low Carbon energy.

Background: Law firm of criminal and family law specialists that have expanded, specialised and modernised their firm since taking over a traditional partnership. Modernising included digitising their work and adopting advanced technology such as AI.

Key factors that drive adoption of advanced technology: value of technology, technology risks, systems alignment, standards and regulation, supply chain dynamics.

Although this business has adopted some advanced technology, they remain risk averse and would be more likely to adopt advanced technology if their insurers or governing body required it. Given the personal and sensitive nature of the information that they handle, they are reluctant to adopt technology that poses any security risk.

However, working in the traditional and established legal industry, this business perceives itself to be ahead of other similar firms when it comes to adoption of advanced technology. They have recently adopted AI to save time on tasks such as summarising evidence, conducting legal research and drafting letters to clients. The partners of the firm were ultimately driven by the potential cost savings of the technology despite some reluctance from some members of the senior leadership team.

If we were saying we’re not forced into doing it, then the issue would be cost and the benefits in terms of is it worth it?

…there is this apprehension about not really knowing…not knowing enough about it to know whether it is safe or not.

Case study 10: Tech Resistor

Mortgage brokerage

Sector: Finance
Size: Small
Typology: Tech resistor

Interested in: Future telecoms, data management and AI.

Background: Local mortgage brokerage that values work life balance and giving back to its local community. They have plans to grow, however, this isn’t underpinned by productivity as they don’t set hourly targets.

Key factors that drive adoption of advanced technology: clarity of use case and value, affordability, leadership attitudes, standards and regulation.

Against the backdrop of regulation that limits the technology it can use and working in a traditional sector, this business doesn’t see the need to adopt any advanced technology. Their knowledge of advanced technology is low, and they are reluctant to innovate or consider new ways of working as they think that their current processes and products are sufficient. They think that the only reason that they would make a change to their technology is if regulation changed or they started feeling strong pressure from direct competitors who were using another product. If this was the case, they would be considering whether the proposed technology would make them more efficient and save money.

We’ve got what we need, and it works. So that’s why we’re not actively looking for anything else.

When everything works as it should do, generally speaking you don’t then go hunting for other solutions. You don’t want to. The thing is…you don’t want to reinvent the wheel.

Case study 11: Detached traditionalist

Fashion Manufacturer

Sector: Manufacturing
Size: Small
Typology: Detached traditionalist

Interested in: Future telecoms, recycling and waste management.

Background: Small, family run business that manufactures fashion trimmings with focus on feathers. An established business where innovation isn’t important because they know that their products have been tried and tested.

Key factors that drive adoption of advanced technology: Clarity of use case and value, perceptions of usability, affordability, leadership attitudes.

A lack of knowledge about advanced technologies and its potential benefits mean that technological innovation isn’t apparent in this business. They do not have a dedicated budget for introducing technology and don’t have any plans to adopt any advanced technology.

They have adopted some technology to “keep up with the times” such as ensuring that their phone lines are up to date, however, they perceive themselves to be a small, established business with basic needs. If they were to introduce new technology, they would be considering its use case, affordability and whether their staff would be capable of adapting to it. Regardless, they would want as little upheaval to their operations as possible.

They would be most likely to consider advanced technology if it was forced on them by regulation or if failure to adopt would result in lost business.

We’re adopting certain things to keep up with the times…but we’re keeping up with what we need to for our business…we’re hardly forerunners in the market of technology.

It’s [advanced technology] not the type of thing that we would go out looking for.

Jibril and Roper, 2025. Factors influencing firms’ adoption of advanced technologies: A rapid evidence review. ↩ ↩² ↩³ ↩⁴
A fuller definition of these clusters is provided in Appendix 2. 5 clusters were considered in the literature review conducted for this project and asked about in interviews, however there was insufficient data to analyse adoption trends of Cluster 5: Life Sciences and Healthcare technologies. ↩
Tornatzky, Louis G.; Fleischer, Mitchell (1990). The Processes of Technological Innovation. Issues in organization and management series. Lexington, Massachusetts: Lexington Books. ISBN 9780669203486;
Oliveira, Tiago; Martins, Maria Fraga (2011). “Literature review of information technology adoption models at firm level”. The Electronic Journal Information Systems Evaluation. 14 (1): 110–121. ↩ ↩²
See Nelles, J., Walsh, K., and Vorley, T. (2022). Transforming Foundation Industries: Engaging SMEs in Innovation. Innovation Caucus;
Nelles, J., Tuckerman, L., Salihu, H., and Vorley, T. (Forthcoming 2025). Lessons from the History of Technology Adoption and Diffusion. Innovation and Research Caucus. Report 016. ↩ ↩²
We note that supply chain dynamics is usually an upstream concern and typically about reliability of supply of inputs required for technology integration. However, in this research the participants referenced supply chains dynamics in similar ways to customer dynamics. ↩
There was insufficiently robust data to include discussion of Cluster 5: Life sciences and healthcare. ↩
We note that the literature review for this project supports this type of intervention. The evidence suggests that generic informational and awareness raising interventions are less effective than tailored evidence, for example providing the business with a benchmark of its technology adoption/performance against that of similar businesses ↩
Innovation Research Caucus ↩
The TOE framework identifies 3 main categories of contextual factors: technological, organisational, and environmental in influencing business decisions. These were drawn on in framing discussions with businesses. ↩
These clusters were chosen to facilitate comparison between different groups of similarly advanced different technologies with comparable use cases. A more granular categorisation would have yielded too few data points in each cluster for a robust comparison. 5 clusters were considered in the literature review conducted for this project and asked about in interviews, however there was insufficient data to analyse adoption trends of Cluster 5: Life Sciences and Healthcare technologies. ↩

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1. Executive Summary

1.1 Background

1.2 Research design

1.3 Catalysts and constraints: key factors driving business adoption decision-making

1.4 Applying lenses: understanding variation in business experiences of catalysts and constraints across the sample

1.5 Conclusions about effective policy interventions to drive business uptake of advanced technologies

2. Research Design

2.1 Background

2.2 Research Design

3. Catalysts and constraints: key factors driving business adoption decision-making

3.1 Exploring the system

Business decision-making: Willingness, Capacity and Capability model

3.3 The 19 factors

Technology factors

Organisation-Level Factors

External factors

3.4 Willingness-Capability-Capacity Summary

4. Applying lenses: understanding variation in business experiences across the sample

4.1 Variation across technology clusters[footnote 6]

For information and communication technologies (cluster 1)

For advanced computing technologies (cluster 2)

For advanced manufacturing and materials (cluster 3)

For Energy and Environmental technologies (cluster 4)

4.2 Variation across sectors

Manufacturing

Retail

Finance

Professional services

Creative businesses

4.3 Variation across key segments in the business population

Pioneers

Strategic adopters

Pragmatic followers

Reluctant adopters

Technology resistors

Detached traditionalists

5. Conclusions: effective policy interventions to drive business uptake of advanced technologies

5.1 Introduction

5.2 Summary of most effective intervention ideas

5.3 Suggestions for support and intervention to increase Willingness, Capacity and Capability

Interventions to increase Willingness to consider a technology

Interventions to increase Capability to implement change.

Interventions to increase Capacity to devote resources

5.4 Suggestions for how to support each business segment

Pioneers

Strategic adopters

Pragmatic followers

Reluctant adopters

Technology resistors

Detached traditionalists

5.5 Putting the findings into action

Appendix

Appendix 1: Full research Design

Background

Aims

Scope

Methodology

Appendix 2: Full list of technologies includes in clusters

Appendix 3: List of possible interventions shown to businesses in the interviews

Appendix 4: Achieved sample

Sample for business interviews

Sample frame for stakeholder interviews

Alignment of the factors with the Willingness, Capability and Capacity model

Appendix 6: Case studies

Case Study 1: Manufacturing

Case Study 2: Retail

Case study 3: Finance

Case study 4: Professional services

Case study 5: Creative industries

Case study 6: Pioneer

Case study 7: Strategic adopter

Case study 8: Pragmatic follower

Case study 9: Reluctant adopter

Case study 10: Tech Resistor

Case study 11: Detached traditionalist

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4.1 Variation across technology clusters^{[footnote 6]}