Policy paper

Interim government response to the AI Champions’ AI Adoption Plans

Published 8 June 2026

Ministerial Foreword

Artificial Intelligence is the defining technology of our lifetime. It has the potential to transform every aspect of our lives: how we work, how we learn, how we treat diseases and how we defend our country. We are in a race for the future, and I believe Britain is in a better position than most to shape this incredibly powerful technology and make it work for all.

That is why my ambition is to make Britain the fastest AI adopter in the G7. But the only way AI will be adopted - far and wide - is if people have the confidence this technology is safe, and if we support people through the changes AI inevitably brings. That includes everyone: not just computer scientists and software developers, but small businesses, freelancers, frontline workers, and people across the entire economy. Our mission is to shape a future that works for all, not just a few at the top.

As part of this effort, we appointed 8 AI champions – brilliant leaders across our priority Industrial Strategy sectors – together spanning everything from life sciences to advanced manufacturing to the creative industries. They have each developed an action plan for their industry, and the government is very pleased to welcome these ideas and we will carefully consider them all. They are the result of decades of experience and extensive listening to businesses and workers about barriers to adoption. They show how AI can be used in everyday settings, and what can be achieved if we give people the tools and the confidence they need to flourish.

I would like to personally thank each of the AI Champions for the work they have put into developing these plans and for the insight and leadership they have shown. I look forward to working closely with them. And their efforts make clear that Britain does not lack innovation or ideas – but that AI is now moving at an incredibly rapid pace, and our response must be every bit as ambitious. That is a challenge I know this country can rise to.

The Rt Hon Liz Kendall MP, Secretary of State for Science, Innovation and Technology

Introduction

AI will transform the global economy, and the UK is well placed to benefit. In 2025, the OECD estimated that AI adoption could raise UK productivity growth by 0.4 to 1.3 percentage points, this would be equivalent to adding £55 billion to £140 billion to UK GVA by 2030.^{[footnote 1]}, ^{[footnote 2]} For businesses, workers and the public, this would mean higher productivity, more rewarding work, and better products and services.

In the UK, much of this opportunity lies in the Industrial Strategy sectors, including financial services, the creative industries and digital and technologies. These sectors are major employers and exporters and are central to people’s daily lives through their products and services. They are also among the sectors most likely to be reshaped by AI. If they adopt AI quickly and effectively, they will boost growth by strengthening their global leadership position, generating new meaningful jobs across the economy and enhancing the products and services they deliver for the public. However, if they move slowly there is the risk that they lose ground to faster-moving overseas competitors and that the benefits on offer are captured elsewhere and do not materialise in the UK.

The real gains from AI will come from deep adoption – this means using AI not just to improve existing tasks but instead to redesign and reimagine how businesses work. Previous waves of technology adoption show that the majority of the benefits went not to those that developed the technology, but to those that adopted most effectively. Today, many firms are using AI to support existing processes, such as drafting emails, carrying out research or writing code. While this can unlock efficiencies, the greater opportunity comes from using AI to transform processes, business models, and products and services. For example, running AI-enabled production lines on the factory floor which adjust maintenance and energy use in real time, or using AI models to support more efficient operation of the electricity system, cutting household bills across the country. This is harder to get right, but far more valuable and it should be the goal for the UK’s leading sectors. Embedding AI deeply into a business is an opportunity to shape work for the better, moving beyond automation and towards a pro-worker model of AI adoption where the technology augments human capability and creates new possibilities for businesses and people.

Deep AI adoption will depend on industry leading from the front and engaging their workforce effectively so they have the right skills and confidence. It’s clear that business leadership matters: emerging data shows that the best managed firms are an order of magnitude more likely to adopt AI.^{[footnote 3]} Workers need the skills, tools and confidence to use AI well, because in many firms it is employees themselves who identify the most practical and valuable uses for these technologies. Evidence from previous waves of technology adoption shows that it happens faster, deeper and more effectively when workers are involved in how technology is introduced and used.^{[footnote 4]}

We asked AI Champions to develop individual adoption plans because we know that sector-specific approaches are critical to driving meaningful adoption. Collectively they have engaged extensively with businesses of all sizes, as well as trade unions and trade bodies, and they have identified case studies of how workers are adopting AI today. The plans being published today include recommendations for how industry and government can work together to accelerate AI adoption across the economy to deliver better outcomes for businesses, workers and young people alike. The Financial Services plan will be published soon, as will a Clean Energy AI Champion review into the opportunities for AI deployment in the electricity networks.

These AI adoption plans are independent and not formally part of government strategy. However, they will inform government policy, and we will draw on them to meet our priorities in the Industrial Strategy Sector Plans and Jobs Plans, and to deliver on the UK’s vision for AI.

Evidence – barriers to adoption and how to overcome them

The prize of getting adoption right in the leading sectors is substantial. The Industrial Strategy sectors have the greatest potential to drive growth.^{[footnote 5]} The OECD projects that all 5 of the sectors with the highest potential for AI-driven productivity gains are in the Industrial Strategy sectors.^{[footnote 6]} They have the potential to benefit workers by creating more rewarding work and improving job quality across the wider economy as workers are empowered with the skills and confidence to use AI effectively.

The government previously set out its ambition to make Britain the fastest adopting AI country in the G7. Currently, the UK’s business AI adoption rate is comparable with its European peers, such as Germany, Netherlands, Belgium and ranks in the top 10-15 countries worldwide for individual AI adoption according to Anthropic and Microsoft.^{[footnote 7]}, ^{[footnote 8]}

Adoption across the 8 Industrial Strategy sectors is increasing. Adoption rates in these sectors are higher than the economy on average, but evidence suggests that intensive adoption across the economy remains some way off.^{[footnote 9]}, ^{[footnote 10]} The AI Champions’ engagement and wider evidence point towards a number of reasons for this:

• A lack of identified use cases - managers need to establish which parts of their business could benefit from AI and how to adjust workflows in response. This is the most frequently cited barrier to AI adoption in DSIT’s research (71% of firms).^{[footnote 11]}
• Lack of skills and expertise across the workforce, from the c-suite to the factory floor. Limited skills and expertise are cited by 60% of firms as a barrier to AI adoption.^{[footnote 12]} Similarly, the Tech Adoption Review highlighted ‘know-how’ barriers as key.^{[footnote 13]}
• External factors, including ethical concerns, high costs and unclear regulations also prevent business adoption.^{[footnote 14]} Policy and regulatory uncertainty featured in nearly 60% of responses to the Technology Adoption Review’s Call for Evidence, driven by a lack of clarity about current rules and the expectation of near-term change.^{[footnote 15]}

Evidence also points towards the most effective approaches for addressing these barriers. Interventions that are targeted towards specific sectors are more impactful than economy-wide measures. This is because barriers to technology adoption vary both between sectors, and within them, particularly by firm size and level of digital maturity.^{[footnote 16]}, ^{[footnote 17]}, ^{[footnote 18]}

Evidence also shows that businesses learn best from their peers within existing networks. The DSIT-supported evidence review into technology adoption found that incorporating a peer group element has generally been effective in both the UK and internationally.^{[footnote 19]} Finally, piloting policies before scaling them helps to identify what works, allowing delivery models to be refined and avoids costly failures.

The AI Champions’ recommendations on how to drive AI adoption

Each sector is unique – and a key insight from the AI Champions’ reports is how important the sector and business context is in driving meaningful adoption. Nevertheless, a range of common themes emerged across several of the plans:

• Reflecting the evidence, time and time again businesses and workers told the AI Champions that the key challenge was identifying impactful AI use cases and that this hindered adoption. Businesses said that peer-to-peer networks can help, and this is reflected in the AI Champions’ plans. For example, techUK have agreed to work with Katie Gallagher, Digital and Technologies Sector Champion, to develop an AI use case library to capture and share AI use cases across the tech sector. Chris Dungey, Advanced Manufacturing AI Champion, proposes AI Lighthouse Factories, leading manufacturing sites that use AI across their operations at full scale, to showcase successful AI deployments and diffuse learning through supply chains in the sector.
• Targeted skills and cultural change programmes feature prominently in the AI Champions’ sector plans. Proposals include industry-led and government backed initiatives to upskill people from the boardroom to the frontline. The plans also identify that this is where support from trade unions could be particularly impactful. In the Creative Industries Sally Davies proposes courses and capability programmes to build AI skills across workers and leaders. Further, Chris Dungey’s plan for Advanced Manufacturing makes it clear that scaling AI adoption can be less about the AI model and more about whether workers can interpret and act on AI outputs. The plan proposes a Manufacturing AI Skills and Culture Campaign with targeted programmes for engineers, operators, managers and leadership teams.
• We must safeguard routes into the job markets and promote entry-level jobs. This will enable us to harness the talent of our most AI literate generation, allowing businesses to strengthen their workforce and providing sustainable job prospects for our young people. The plans recognise the importance of promoting adoption that augments and empowers junior roles, rather than replacing them. For example, Katie Gallagher proposes an Early Careers Jobs Alliance in the Digital and Technologies sector. This will bring together leading businesses and trade unions to address this issue – exploring how to ensure the resilience of our pipeline of future talent into the sector, and to provide young people with the best opportunities. We will look to scale this initiative quickly to other Industrial Strategy sectors if successful. Further, David Hallett suggests a tiered approach to upskilling, with union-approved training targeted at different groups of workers in the Life Sciences sector, including those in the most junior roles, to understand how AI tools can be embedded into their day-to-day roles.
• Fragmented and poor data readiness is a systemic constraint to AI adoption, with a lack of practical guidance on data use and uncertainty around governance also slowing things down. To address this in the Life Sciences sector, David Hallett has proposed establishing a National Data Pooling Consortium to pool preclinical and human data from multiple sources, which would enable researchers to run AI models on NHS data within secure environments. In the Digital and Technologies sector – where there are pockets of strength on this issue – Katie Gallagher proposes producing an AI Adoption Operating Framework. This would draw on expertise across the sector to support businesses with insight and guidance on improving data access, quality and governance.
• Clarity on the regulatory landscape also emerged as a top priority for businesses in highly regulated industries such as Professional Business Services. Shaheen Sayed will spearhead efforts to ensure the UK’s regulatory framework remains secure, innovation-ready and fit for the age of AI in the professional services sector. This will bring regulators and industry together to deliver clear, evidence-based recommendations to ministers on regulatory changes and practical steps required to drive innovation across Professional Business Services firms.

Government’s interim response

Government welcomes the publication of the AI Champions’ sector adoption plans and thanks the Champions for bringing forward their industry and worker-led perspectives. These plans are a critical step forward and make an important contribution to government’s evidence base on how to ensure trusted, effective and safe adoption across the Industrial Strategy sectors. The plans will help deliver real impact for Britain’s businesses and workers to ensure that AI works for everyone – including through the upcoming Jobs Plans that bring together government, industry, unions and others to address workforce challenges in each sector.

The recommendations across the plans are well aligned on one point: that this is the time for strong industry leadership. The UK business community can and must lead from the front - demonstrating how to drive high-impact, pro-worker AI adoption in practice. Safe, trusted AI is critical to widespread adoption as well as meaningful engagement with the UK workforce. The AI Champions’ plans set out a clear and compelling vision for how to do this. Now, the task is collective, and we call on industry to back the AI Champions’ vision, and match it with ambition and action.

The government has ringfenced a new package of support that will make it easier for businesses to test, adopt and scale AI, as well as support workers and open up opportunities for young people. Schemes backed by over £200 million will include investment into skills, local communities and industry to drive responsible AI adoption, removing the barriers holding back AI adoption for businesses of all sizes. We expect that this funding will support the delivery of leading proposals from the AI Champions’ sector plans.

This includes providing £20 million to support the development of the new Early Careers Jobs Alliance, which will be co-chaired by the Digital and Technologies sector AI Champion, Katie Gallagher OBE, and the General Secretary of Prospect, Mike Clancy. This will bring together groups like employers, trade unions, training providers, researchers and young people to reimagine what early career jobs should look like in the AI era. The Alliance will focus on ensuring that young people have opportunities for fulfilling career pathways in high-growth, AI-enabled sectors, with structured training, progression and long-term opportunity at their core.

The Alliance will be integrated into the Jobs Plans and wider Industrial Strategy and act as a practical mechanism for trade unions, employers and young people to respond to the opportunities and disruptions AI presents to early career jobs in those sectors. It will respond to challenges articulated in forthcoming Jobs Plans and provide practical evidence and recommendations, enabling close coordination with other government skills and jobs initiatives such as TechFirst and the Youth Guarantee. This Alliance will start with a focus on the Digital and Technologies sector but should be a blueprint for other sectors of the economy facing the same challenge, such as Professional Business Services.

The wider package will back British AI and help ensure that AI works for everyone, creating new opportunities for businesses of all sizes and across all sectors, as well as better jobs and stronger skills across the UK.

We are doing this by:

1. Building a strong evidence base and spotlighting good practice:

• Nobel Prize-winning economist Simon Johnson will chair a new AI Economics Institute to track how AI is changing jobs and growth, with businesses committing to sharing data to help shape future policy via the AI Adoption Summit Data Sharing Agreement.
• A new Pro-Worker Adoption Prize – also chaired by Simon Johnson - will recognise, reward and celebrate UK organisations that are adopting AI in ways that support workers. This will raise awareness of practical, pro-worker use cases and address one of the key barriers to wider AI adoption in the UK: limited knowledge of how AI can be used effectively, alongside skills and trust constraints.

2. Supporting the workforce through AI transformation, and promoting opportunity for young people:

Alongside launching the new Early Careers Jobs Alliance, we are:

• Making AI skills accessible to everyone through AI Skills Boost. In partnership with leading industry experts, we are providing free, high-quality online training for all UK adults, designed to build practical, workplace-ready skills. Through this initiative, we are committed to upskilling 10 million workers by 2030, helping our workforce best take advantage of the opportunities of AI while also preparing for its impact. Over 1.7 million courses had already been delivered to workers across the UK by April.
• Providing £200 million in funding for opportunities for young people to gain skills for a career in tech through DSIT’s TechFirst programme. This includes delivering AI and tech training to 400,000 young people in the UK’s most disadvantaged schools, and piloting new training pathways in the North West and North East of England later this year. This is backed by leading industry partners. If successful, these pilots will expand nationwide so they can meet the needs of young people across the country looking to forge a career in tech.
• Expanding the Spärck AI Scholarships programme with £4 million of backing in order to sponsor 50 industry placements for top university scholars within innovative startups or give them the skills to start their own businesses. We will work with partners across industry and we are pleased that new organisations are now backing the scheme including: BT, HSBC, LSEG, National Grid, Octopus Energy, WPP, and Universal Music Group. They join alongside our existing Anchor Partners AISI, Beamery, CausaLens, Darktrace, Faculty, Flok, i.AI, PolyAI, and Quantexa.

3. Backing British AI innovators so their trusted tech is adopted across the economy:

• Innovate UK’s BridgeAI programme will focus on the Industrial Strategy sectors, linking British AI companies with businesses looking to use AI products and tools. Together, they will be able to apply for grants from a £100 million fund to test advanced AI tools in live operational environments – getting British businesses measurable results from cutting-edge British AI makers.
• A new advisory AI Growth Lab will bring together businesses, regulators and experts to work together to trial AI in real working environments - starting with legal services. This will give firms clear, practical information on how to responsibly adopt AI while meeting regulations.
• An AI Assurance Stakeholder Consortium will develop guidance and best practice to support the sector’s development and help deliver AI people can trust. Boosting trust is essential to encouraging and enabling AI adoption. The initiative has the backing of BCS, the Chartered Institute for IT. This builds on our work to establish a new Centre for AI Measurement in the National Physical Laboratory to be at the cutting edge of developing AI assurance techniques.

Next steps

Government is not standing still. We are committed to continuing to work with the AI Champions to help turn these plans into action and we urge industry to do the same. This is a time for leadership, and businesses in every sector must step-up and engage with the AI Champions and their plans, invest in their workforce and lead transformation in their sectors.

We will reconvene with the AI Champions every quarter during the remainder of their term, refining ideas, tracking delivery and pushing the AI Champions’ most promising proposals from sector focused pilots into scaled programmes across the broader economy.

This is urgent, high-stakes work. Getting AI adoption right will take sustained leadership and genuine partnership between government, industry and workers. If we succeed, we can unlock growth, create new and better jobs and raise opportunity across the country.

1.  Macroeconomic productivity gains from Artificial Intelligence in G7 economies (EN) ↩

2. For methodology see AI Skills Boost: explainer - GOV.UK ”What is the potential impact of AI on UK productivity?” ↩

3.  Management practices in the UK: 2016 to 2023, Office for National Statistics (2024) ↩

4.  The Pissarides Review - IFOW ↩

5.  Sector Plans - GOV.UK ↩

6.  Macroeconomic productivity gains from Artificial Intelligence in G7 economies (EN). See Figure 10. ↩

7.  Eurostat, ONS BICS ↩

8.  Microsoft AI Diffusion Report; Anthropic Economic Index ↩

9.  Business Insights and Conditions Survey (BICS) Wave 92 to 147, Artificial Intelligence (AI) Adoption Ad Hoc Tables: Department for Science, Innovation and Technology - Office for National Statistics. See “Requested SICs” for specific industry definitions. Note: this survey does not include finance firms, and these SIC codes are reported at a higher level than sectors are typically defined, therefore analysis should be treated as indicative. ↩

10. Briefing paper No. 9 Forecasting productivity ↩

11.  AI Adoption Research - GOV.UK ↩

12.  AI Adoption Research - GOV.UK ↩

13.  Technology Adoption Review - GOV.UK. The review’s internal and external barriers highlight the importance of organisational change costs and the lack of information on technology benefits and risks. ↩

14.  AI Adoption Research - GOV.UK ↩

15.  Technology Adoption Review 2025 ↩

16.  AI Adoption Research - GOV.UK. For example, unclear regulation was more likely to be reported as a significant barrier preventing the adoption of AI by those in finance and real estate (81%). ↩

17. Ibid. For example: high cost was more likely to be cited as a significant barrier by large organisations (90%) and less likely to be reported by micro businesses (72%). ↩

18. Cirillo et al. (2023) The Adoption of Digital Technologies: Investment, Skills, Work Organisation: Adoption decisions reflect firms’ internal resources and existing technological capabilities. ↩

19.  Factors influencing firms’ adoption of advanced technologies: A rapid evidence review - GOV.UK ↩