Research and analysis

AI adoption survey report 2026: executive summary

Published 29 October 2026

Introduction

The Department for Science, Innovation and Technology (DSIT) published the AI opportunities action plan in January 2025 and sector-focused AI adoption plans in June and July 2026. As part of this, DSIT set out an ambition to embed artificial intelligence (AI) across the UK economy.

Understanding the current state of AI adoption and the growth rate over time is a vital piece of evidence which will help to ensure that the action plan’s objectives are achieved.

In early 2025, DSIT commissioned the first wave of research into UK businesses’ use of AI and the barriers businesses face. This second wave of research revisits the same topics to explore:

• how levels of adoption have changed
• whether barriers have been overcome or new barriers have emerged
• businesses’ support needs

The research consisted of:

• a quantitative survey of a representative sample of UK businesses
• follow-up in-depth interviews to further explore topics raised
• case studies with adopters to explore the practicalities of AI adoption

The survey used computer-assisted telephone interviewing (CATI) between 7 January and 21 April 2026 to achieve 3,503 interviews with businesses (see the ‘Methodology’ section of the full report for more details).

Fifty follow-up in-depth interviews were conducted with businesses who had taken part in the survey and agreed to be contacted to take part in a further follow-up interview.

The interviews were conducted by phone or online via Microsoft Teams and explored businesses’ thoughts on, and use of, AI in more depth.

They were supplemented by 7 ethnographic site visits to businesses who had adopted AI. These site visits have been reported as case studies.

Main findings

AI adoption

AI adoption doubled since 2025. In 2026, one-third of UK businesses were using at least one AI technology (32% compared to 16% in 2025). Adoption remained uneven by sector and business size, with higher uptake among larger firms (52%) and knowledge-intensive industries such as:

• information and communication (61%)
• real estate (45%)
• business services and administration (39%)

Use was concentrated in accessible, low-complexity tools, particularly natural language processing and text generation. This included the use of Large Language Model (LLM) based approaches (77% of those using or planning to use AI).

AI became more embedded in day-to-day operations, most commonly in:

• administration (81% of those using or planning to use AI)
• marketing (71%)
• IT functions (66%)

The main driver of adoption was improving efficiency and productivity (71%), followed by improving employee experience (27%), and gaining competitive advantage (25%).

Over half of adopters (57%) reported using AI constantly, with 27% using it at least weekly. Most businesses were still in an early or exploratory stage, with gradual progression towards more advanced use cases.

Expenditure on AI remained relatively modest for many businesses, with 47% of those able to estimate expenditure reporting no expenditure in 2025. This reflects the widespread use of free tools or AI features embedded within existing software. Where spending occurred, it increased with business size, and overall investment grew significantly over the past 5 years.

Impact of AI

AI delivered measurable but largely incremental improvements. The most commonly reported benefits were:

• improvements in workforce productivity (71%)
• the development of more efficient or flexible processes (60%)

Half of adopters (50%) reported an overall increase in productivity, although these gains were generally described as modest. The most common benefits related to task automation and workflow optimisation, rather than transformational change.

Operating cost impacts were mixed. While some businesses reported reductions (24%), many had seen no immediate financial effect (64%), and a minority reported an increase (9%).

Perceived strategic importance of AI remained moderate, despite widespread usage. Only 14% of businesses considered AI tools to be of high or critical importance to their operations.

Overall, AI was functioning primarily as a support tool, augmenting existing activities rather than redefining business models.

Barriers to AI adoption

The most significant barriers were capability-related, including limited:

• skills
• expertise
• understanding of AI use cases

Limited AI skills, expertise or knowledge affected 67% of businesses that had adopted AI, and 78% of those planning to adopt it. A lack of a clear business case or proven return on investment was cited by many businesses, particularly non-adopters (65%).

Concerns around accuracy, bias, data privacy and security continued to limit adoption. 56% of businesses who had adopted AI, and 60% of those planning to use AI, said they had concerns about bias and lack of accuracy.

While cost was a factor, it was more commonly associated with the time, effort and resource required to implement and embed AI, rather than the direct cost of tools themselves.

Regulatory and sector-specific uncertainties also contributed to cautious adoption, particularly in regulated industries such as:

• finance
• legal
• transport
• healthcare

In these industries, organisations handle sensitive data and compliance and liability risks were felt to be more significant.

Future plans for AI

Businesses expected continued growth in AI adoption. 31% of businesses using or planning to use AI said they expected more than half of their staff to be using AI in the next one to two years. This compares to 22% who reported more than half of their staff were already using AI.

Investment in AI was expected to increase overall, with 65% of businesses anticipating an increase in AI-related budgets. However, this increase was expected to vary across business sizes and sectors. Planned investment was focused primarily on:

• implementing off-the-shelf applications (61%)
• automating tasks (57%)
• embedding AI into existing systems (54%)

Interest in more advanced technologies was growing, although adoption remained at an early stage. For example, 24% of businesses using or planning to use AI were planning to adopt machine learning.

Future adoption was likely to remain incremental and staged, with continued reliance on testing and piloting. There was a clear trajectory towards deeper integration of AI into core business functions over time.

Perceptions of trust and safety in AI

Trust in AI systems remained cautious and conditional. Most businesses (81%) reported applying some level of human input or oversight to AI-generated outputs, although this had declined slightly since 2025.

Trust varied by use case, with AI widely accepted for low-risk, routine tasks such as drafting or summarising content, but less trusted for high-stakes decisions or autonomous processes. More advanced technologies, particularly agentic AI, were less widely trusted and more likely to be subject to scrutiny.

The main concerns were:

• accuracy
• transparency
• data security
• regulatory uncertainty

Another concern was the perception of AI as a ‘black box’ system where the internal logic or workings cannot be seen by users.

As a result, AI was typically used as a tool to support decision-making rather than replace human judgement, with responsibility for outcomes remaining firmly with users.