The Confidence Code by Federation of Small Businesses

The Confidence Code

The challenges and opportunities of AI for small businesses

Acknowledgements

This report was written by Iliana Pearce, Policy Advisor for technology and innovation. Special thanks to FSB’s policy, government affairs, and media and communications teams, in particular: Anna Slater, Deputy Head of Media; Padraig Blee, Government Affairs Advisor; and Chris Russell, Senior Policy Manager. Special thanks also to the

Who we are

The Federation of Small Businesses (FSB) is the UK’s grassroots business organisation. We are a crossparty non-profit body that represents small business and self-employed members in every nation and region.

For over 50 years, we have been the authoritative voice on policy issues affecting the UK’s 5.7 million small and medium businesses, microbusinesses and the self-employed. FSB is the UK’s largest business group and leading business campaigner, focused on achieving change which supports smaller businesses to grow and succeed.

We also provide our members with a wide range of vital business services, helping them to start, run, and grow successful businesses through high quality protection and support. This includes 24/7 legal support, financial expertise, training and events, debt recovery and employment/HR advice – alongside a

members of FSB’s Innovation Committee and their Chair, Satheesh Pillai. Thank you also to all the FSB members who fed into this work.

The report was designed by Cactus Design Limited –a small business based in Wales.

powerful voice heard by governments at all levels. Our local, national and international campaigning helps shape policy decisions that have a direct impact on the day-to-day running of smaller businesses. We work for their interests through research and engagement with our members, and by effective campaigning – influencing those in power through policy analysis, government affairs, and media and public relations activity.

Our policy and advocacy work starts with our expert team in Westminster, which focuses on UK and England policy issues, the UK Government, Parliament and the media. Further to this, our teams in Glasgow, Cardiff and Belfast work with governments, elected representatives and media in Scotland, Wales and Northern Ireland.

Foreword

The last year has seen an increasing shift in focus towards the economic benefits of widespread AI adoption, rather than viewing it as a ‘winner takes all’ scenario. This report shows exactly how tech adoption can translate into meaningful impacts for small businesses.

Small firms are seeing different outcomes to what they initially expect. They’re adopting tech to cut costs and improve efficiency, but as tech gives business owners more time and headspace, businesses often end up being able to grow. The impact of tech on the small businesses that adopt it is shaped less by the ‘why’, and more by the ‘how’. Engaging with staff, providing training, and having a clear plan for implementation are particularly impactful.

The UK economy has much to gain from having tech-enabled businesses across every sector. The world is changing, as is the way small businesses operate. What this report shows is that it’s really know-how and understanding that’s the strongest barrier to general tech adoption, and even knowing where to start can be a massive hurdle. Technology can also be a valuable tool for inclusion, whether making businesses’ websites more accessible through AI-augmented British Sign Language (BSL) interpretation, or allowing those who are unemployed to set up dynamic businesses across the economy.

When we first asked small businesses about AI in 2023, 73 per cent had concerns about the tech in relation to the business; now, this has risen to 92 per cent. And the real impact of this is being seen in the ways small businesses feel comfortable using AI. Concerns span trust in providers, data privacy, compliance, Intellectual Property (IP), and emerging security threats. Female entrepreneurs are being especially hard hit, with a more risk-averse approach

to adoption resulting in them seeing lower average revenue impacts from AI. Small firms are being held back from AI adoption by very real concerns and uncertainties. Addressing these challenges now is key to making sure small businesses are able to make the most of this new technology.

The UK is primed to nurture innovative, ethical AI firms, grounded in what people and businesses actually need. Enforcing copyright, discounted access to AI compute, and a national body for open source could all make a real difference.

The technology is evolving quickly and no one has all the answers. But in a time of uncertainty we need a combination of decisive action to mitigate immediate harms for small businesses, support to help build capacity for responsible adoption of AI, and to build our regulators’ capabilities and agility. Each of these is key to making sure the UK’s small businesses are able to make the most of the opportunities that new technology presents.

Satheesh Pillai Policy Champion, Tech Federation of Small Businesses

Key findings

55%

of small businesses use AI, up from 20%

92%

of small businesses have concerns about AI, up from 73%

60%

of small businesses that do not use AI say they do not trust AI providers to handle their data responsibly

Small businesses that adopted AI in the last 12 months saw an average resulting increase in revenue of 3%

An extra £42 billion could be added to the UK economy each year if half of small businesses currently not using AI adopted it, and existing users increased their use by 50%

31%

of small businesses say that support to adopt AI legally, ethically or responsibly would help them use it with confidence

Female entrepreneurs are more concerned about legal liability and risk due to AI (38%) than male entrepreneurs (27%)

34%

of small businesses say better guidance on how to implement technology would incentivise them to adopt it

Recommendations

The UK Government should:

• Build a ‘Responsible AI Essentials’ programme modelled on the National Cyber Security Centre’s Cyber Essentials.

• Introduce responsible AI adoption vouchers to help small businesses achieve Responsible AI Essentials certification.

• Continue to build out the AI Skills Hub with a focus on clear and transparent credentials for users, so a user can track their level of development on their profile against each of the core skills.

• Introduce upstream regulation of large tech firms, requiring them to mitigate risks presented by AI in relation to its use in business contexts.

• Develop a responsible AI adoption course for small business owners that is governmentfunded and endorsed.

• Mandate AI content labels for large AI developers and online platforms.

• Give the Intellectual Property Office powers to proactively investigate large-scale breaches of copyright in relation to AI and deliver regulatory enforcement.

• Establish a national body with responsibility for stewardship of the UK’s open source industry.

The Department for Digital, Culture, Media & Sport should:

• Broaden the remit of Ofcom to include regulation of cloud services in the same way that utility providers are currently regulated.

• Convene a taskforce with industry and small businesses to look at providing a one-clickswitch experience for businesses moving their data from one cloud infrastructure provider to another.

• Introduce grants for small businesses to make their services more accessible using technology.

The Department for Business, Innovation, Science & Trade (DBIST) should:

• Introduce a Code of Practice to support employers to engage with their staff when introducing new technologies such as AI.

• Introduce incentives for AI data centres to provide their own energy generation.

• Develop a tech adoption and digital skills diagnostic tool, housed on the Business Growth Service website and linked with responsible AI adoption vouchers and the AI Skills Hub.

HM Treasury (HMT) should:

• Introduce a ‘technology adoption and productivity tax relief scheme’ based on R&D tax credits for Corporation Tax.

• Commit to not introducing a Minimum Expenditure Threshold (MET) which would exclude the smallest innovators from accessing R&D tax credits.

The Department for Work and Pensions (DWP) should:

The Digital Regulation Cooperation Forum (DRCF), led by the Information Commissioner’s Office (ICO), should:

• Publish a set of ‘AI model cards’ with key information about the most widely-used AI tools.

The Intellectual Property Office (IPO) should:

• Create a new and exclusive IP right to the voice and/or image of an individual, to prevent their exploitation by others for commercial or criminal purposes through the use of deepfakes.

Ofcom should:

• Work to extend protections already offered to microbusinesses to businesses with up to 50 employees, in relation to telecoms.

• Local authorities should:

Local authorities and Business Improvement Districts (BIDs) should:

• Establish high streets-focused digital adoption programmes focused on basic digital adoption, with an additional ‘bricks and clinks’ strand to support high street retailers to establish or enhance their online offerings.

Innovate UK should:

• Resume Smart Grants with increased funding.

The Chartered Institute for IT should:

• Introduce an accreditation scheme for software integrators.

Primes in supply chains should:

• Introduce specific technologies or build their cyber resilience measures if they decide to impose requirements for their suppliers. Primes should use their resources to provide advice and support to small businesses in their supply chains.

Chapter 1 - The lay of the land: The state of digital adoption among SMEs

Small businesses’ adoption of AI has risen considerably since September 2023 such that over half (55%) of small firms now use the technology. Sectoral adoption gaps remain relatively stable, with a sustained gap between ‘early’ and ‘later’ adopting sectors (see Figure 3, below).

Use of both cloud computing and data analytics has also risen, whereas use of other tech such as eCommerce and customer relationship management software (CRM) remains stable.

Figure 1: Small business tech adoption from January 2023 to November 2025

Sources: FSB technology adoption survey, January 2023; FSB Small Business Index survey, September 2023; FSB AI & tech adoption survey, November 20251

Use of AI

Figure 2: Ways in which small businesses use AI

Source: FSB AI & tech adoption survey, November 2025

Draft or edit written content (other than emails)

Review or summarise documents

Create marketing content

Generate ideas

Draft or edit emails

Generate or edit images

Take notes in meetings

Reduce the need for outsourcing

Develop new products or services

Analyse trends or make projections

Generate or edit videos

Draft applications for government support

Identify AI-generated content

Choose suppliers

Other Recruitment

Our data also shows that six per cent of those deploying AI use sector-specific AI tools, and four per cent use proprietary or bespoke tools created for or owned by their business.

Younger businesses are markedly more likely to use AI than those that have been running longer; with 90 per cent of businesses 4 years old or younger using AI, 63 per cent of businesses aged between 5 and 19, compared to only 45 per cent of those that have been running for 20 years or more. This likely reflects the fact that younger organisations will not have legacy software systems in place, so can build or pivot their tech stacks with AI in mind. They may also be smaller and more agile, able to more easily adjust business processes and ways of working to make the most of AI.

While only 10 per cent of AI users used AI to help draft applications for government support, FSB’s procurement research shows that 20 per cent of small businesses that have submitted a bid to another organisation used generative AI or text generation technology.2 Although not directly comparable to bids for overall government support, this does suggest that the figure of those using AI to support applications for government support is likely to be higher than 10 per cent among those who are applying for the support.

Qualitative research also showed that small businesses are using AI as a starting point to help draft applications for awards and certifications.

“There are a lot of awards and competitions out there. They can be really helpful for your business, if you can get them. But when there are five areas and you have to write 1,200 words for each it can be quite daunting. Being able to drop your business plan into AI and ask it to have a go at answering the questions is great – I always write the applications myself, but the AI picks up things I would have missed, and we end up submitting a better application. Getting these awards and recognitions means we’ve really been able to focus on the tourism side of our business. We’re hopefully going to be able to expand our business as a result.”

Sarah Saunders, Black Shuck Distillery, East of England

Some of these applications of AI are more involved than others, with uses such as drafting or editing emails and taking notes in meetings requiring less technical expertise and rethinking of existing processes than others, such as developing new products and services. 50% of small businesses use AI for more basic applications, making up 90%

of those that use AI. A lower proportion use AI for more advanced applications, reflecting 38% of small businesses and 69% of AI users. As we will see later (Chapter 2), the tasks that small businesses choose to use AI for are closely associated with the resulting impacts to revenue and productivity.

Source: FSB AI & tech adoption survey, November 20253

Figure 3: AI adoption by sector

Sectoral use of AI

We see that sectoral gaps in AI adoption remain relatively stable compared with 2023 levels. Sectors that were leading in 2023, professional, scientific and technical services, information and communication, and the creative industries, continue to have a lead over manufacturing, construction and wholesale and retail. These later adopting sectors are starting to use the technology, but a question remains over the extent to which AI is useful for different sectors. Use of sector-specific tools is highest for the information and communication sector, with 12 per cent of AI users in this sector using sector specific tools, relative to six per cent of AI users across all sectors.

Qualitative research with small businesses suggests that some sectors are adopting more slowly in part because much of the physical work of the sector cannot be done as easily by AI. Where technology is used, this is often to help with business support

Use of AI across the nations and regions

Figure 4: AI adoption by nations and regions

Source: FSB AI & tech adoption survey, November 20254

functions (e.g. finance, HR, etc.) rather than a business’ revenue-generating activities. Indeed, the top three use cases are broadly consistent across sectors (as outlined in Figure 2), and relate to activities likely to form part of business support functions. The exceptions are wholesale and retail (for which reviewing and summarising documents is replaced by editing and drafting emails) and construction (for which creating marketing content is replaced by helping generate ideas).

“What it comes down to with AI at the moment is: in your day-to-day job, are you in front of a screen?”

Satheesh Pillai, FSB member, Entropy Advisors Ltd, London

The regional differences outlined in Figure 4 may be may be due to higher than average density of high-adopting sectors in London. Qualitative research also suggests that the higher rates of AI use among London-based small businesses may reflect networking effects. The density of small businesses, ease of in-person networking, and prevalence of coworking spaces may allow for greater sharing of innovation between small business owners.

“The thing with London is that the business community here is really concentrated, so the networking effects are strong. You notice quite quickly if your competitors are doing something you’re not.”

Satheesh Pillai, FSB member, Entropy Advisors Ltd, London

Disabled entrepreneurs’ use of AI

Disabled entrepreneurs are less likely than their peers who are not disabled to say that they use AI (49% compared to 57%), and are slightly less likely to use it for specific use cases such as editing or drafting written content other than emails (29% / 37%). However, they are slightly more likely to use AI to identify AI-generated content (9% / 5%).

Small business adoption of other digital technologies

Adoption in the last 12 months

Use of data analytics tools has risen by 10 percentage points since September 2023 (33% to 43%) with most of this growth in the last 12 months. Usage increases with business size, from 36 per cent for the self-employed (0 employees) and 44 per cent for micro businesses (1-9 employees) to 48 per cent for small businesses (10-49 employees). Businesses based in London are markedly more likely to use data analytics tools (54%), followed by the East of England (53%) and West Midlands (52%).

Non-AI

technology use by sector

We see a different story for cloud computing, which has risen in usage by 19 percentage points (from 29% to 48%) since September 2023. London is the only area substantially more likely than average to use this technology, at 61 per cent. We see that eight per cent of businesses have concerns about being able to access relevant business data when they need it, a concern that is unlikely to be linked to AI as it sits at 8 per cent and 9 per cent for users and non-users of AI respectively.

Figure 5: Percentage point change in use of non-AI technology between 2023 and 2025

Source: FSB technology adoption survey, January 2023; FSB AI & tech adoption survey, November 2025

Urban and rural businesses

There seems to be quite a divide between urban and rural businesses in terms of technology uptake.

Urban businesses were more likely than their rural counterparts to use a CRM, at 28 per cent relative to 19 per cent, and similarly more likely to use cloud computing platforms (51% / 43%) and data analytics (46% / 39%).

This may reflect differences in connectivity difficulties experienced by those in urban premises relative to rural premises, which are cited as a barrier to adopting technology by only 6 per cent of urban businesses, but 15 per cent of rural businesses. Connectivity is particularly important for cloud-based services as well as data analytics tools.

Indeed, FSB research shows that while almost half (49%) of small businesses say their broadband speed has been fast over the last 12 months,5 this falls to 43 per cent for those based rurally. Rural businesses are also more likely to say that their connection speed has been slow, at 18 per cent, relative to 9 per cent of urban businesses and 11 per cent on average.

In terms of specific challenges relating to broadband, urban and rural businesses are as likely as each other to have had difficulties with factors relating to customer service, such as high costs (14% of urban / 15% of rural), unexpected price increases (8% / 7%) and bad customer support (13% / 11%). However, factors linked to connectivity are more likely to vary by location. Unreliable connection is cited by 23 per cent of urban businesses and 30 per cent of rural, while difficulties downloading and uploading files are cited by six per cent and 10 per cent of urban and rural businesses respectively. Use of non-locally-based AI relies heavily on connectivity, and particularly download and upload speeds, suggesting that connectivity challenges may partially explain why 59 per cent of urban-based businesses use AI relative to 50 per cent of rurally-based businesses.

Chapter 2 - Making the business case: Impacts of technology on adopting businesses

Small businesses adopt technology for a range of reasons, the most oft-cited of which relate to efficiency and cost savings, but for 17 per cent of adopters it has allowed them to expand their businesses. How small firms use AI is shown to have a particularly strong link to the impact it has. Small businesses that use AI for more innovative, revenueraising activities see greater productivity and revenue gains than those who use it primarily to find efficiencies in existing processes. AI also appears to have a complementary effect on non-AI technology, with AI users seeing higher productivity and revenue gains as a result of using non-AI technology than those that do not use AI.

I am convinced that AI will lead to a renaissance of small business across our country.

Why? Because you can be nimbler and move faster than big businesses. You know your whole business so well that you are better placed to see how AI can help every part of it. It can help you do more with less, be your catalyst for growth.

Investing in AI is investing in your business’s future.

This report shows small businesses how they can adopt AI to make it their superpower.

Our shared challenge is to find ways to use AI to make your businesses, Britain’s small businesses more competitive, more innovative, more ambitious than they have ever been before.

The Rt Hon Rishi Sunak MP, former Prime Minister of the UK

The why: Motivations to adopt technology

Small businesses have many motivations for adopting new technologies, but as Figure 6 outlines, the predominant ones are productivity-related.

Those that use AI were more likely to cite every individual motivation across the board than those that don’t use AI. These gaps were particularly substantial for motivations likely to be associated with AI, such as working more efficiently (a gap of

32 percentage points) and automating tasks (38 percentage point gap). Motivations associated with innovation, such as developing new products and services and initiating new business models, also saw notable differences between those that do and do not use AI. The differences sit at 27 and 17 percentage points respectively, with AI users citing each one more.

Figure 6: Small business motivations for adopting technology

Source: FSB AI & tech adoption survey, November 2025

Work more efﬁciently

Ability to automate tasks

Improve products or services

Improve customer experience

Provide cost / budget savings

Keep up with competitors

Develop new products or services

To gain insights into my customer base

Initiate new business models

Reduce staff levels

Don’t know

Business expansion plans do not always drive adoption – but growth is often a result

A total of 17 per cent of those that adopted new technology were able to expand their business as a result of doing so. This goes up to 22 per cent for those that use AI (8% for those that do not).

Motivations for adopting technology that are most strongly associated with a business eventually being able to expand their business as a result of that technology are:

• being motivated to work more efficiently (89% of those that were able to expand their business)

• to improve products or services (69%)

• by the ability to automate tasks (66%)

• to improve customer experience (64%)

• to provide cost/budget savings (48%).

Interestingly, this includes a mix of both more operations-focused motivations, such as increasing efficiency and driving down costs, as well as those more closely associated with innovation, such as improving products, services and customer experience. This suggests that while small businesses may not be primarily motivated to adopt technology by the potential to grow their business, this is often an outcome in practice.

The how: Steps taken to support adoption

Subscribed to ready-to-use/external software

Developed technology in-house

Gathered ideas and feedback from employees

Provided training for employees

Developed a plan for implementation

Outsourced software development or integration

Developed an AI policy

Supported by government business support services

Supported by government tech adoption programme

Supported by local universities

Figure 7: Steps taken by small businesses in adopting technology Source: FSB AI & tech adoption survey, November 2025

Less than one per cent of small businesses using technology have received support from local universities to adopt the tech, and only four per cent received support from government-funded services. Support was more likely to have come from general government-funded business support services, such as Growth Hubs and Help to Grow Management (3%) than through a government-funded programme aimed at supporting tech adoption (1%), although percentages for both are very low.

While some small businesses are consulting with their staff and developing an implementation plan, this is not the majority. The next section outlines the strong benefits associated with taking these steps. It is clear that small businesses would be better able to adopt technology, and adopt it more impactfully, if they had more support to do so.

Steps to adoption and impacts of technology for the business

Not all businesses that adopted technology in the last 12 months saw productivity or revenue gains as a result. 59 per cent of those that have adopted AI in the last 12 months have seen a resulting productivity gain, and less than a quarter (24%) saw revenue gains. A similar proportion of those that adopted non-AI technologies saw resulting revenue gains (25%), although fewer of this group saw resulting productivity gains (40%). The steps taken when adopting technology appear to be linked to whether a business sees productivity and revenue gains as a result.

Figure 8: Steps taken by small businesses in adopting technology, by impact on revenue

Source: FSB AI & tech adoption survey, November 2025

Gathered ideas and feedback from employees

Provided training for employees

Developed a plan for implementation

Developed an AI policy

Supported by government business support services

Supported by government tech adoption programme

No steps taken

Figure 8 shows that engaging with employees, including through training, is the type of adoption step most closely associated with seeing revenue gains as a result of adopting technology. This is the case for adopting both AI and non-AI technology.

The mechanism by which technology is brought into a business is also linked with the impact it has. In-house development of technology is the means of adoption most closely associated with an increase in revenue due to AI, with 40 per cent of this group having adopted through this route compared to 19 per cent of small businesses on average.

Software integrators

Finding a reliable firm to help integrate software into a business can be a challenge. One in seven (15%) of those that have adopted technology by outsourcing software development or integration to a third party say that being unable to find a reliable business to help integrate new software into their business is a barrier to adoption. They are also more likely to highlight costs being too high or uncertain (33% relative to 25% on average) and concerns that technology will not meet expectations (38% / 25%), with meaningful agreement over expectations being highlighted as a particular challenge.

“It is not always clear what has really been agreed until delivery is already underway. By then, change requests, extra costs and difficult trade-offs can mean the business has to give up important features simply to get something live. The software company may not be acting badly, but the small business owner is often left carrying the risk between what they thought they were buying, what actually gets delivered, and whether it creates the value they needed in the first place.”

Jamille Sammour, 5y Technology Ltd, London

The what now: Impacts of technology on adopting businesses

In our survey, we asked small businesses directly how the technologies they had adopted have benefitted their businesses.

Figure 9: Impacts of technology on businesses that adopted tech

Source: FSB AI & tech adoption survey, November 2025

Reduce my workload

Generate cost / budget savings

Expand my business within the UK

Invest in new technology

Used savings to manage cashﬂow

Invest in staff training / upskilling

Reduce staff levels

Expand my business through imports / exports

Invest in assets or capital

Invest in green technology and / or decarbonise

Expand my

Figure 9 and Figure 10 both suggest that increased productivity is the most common benefit businesses experience with technology adoption, rather than business growth. The top impact of introducing technology has been to reduce workload (46%), which holds separately for businesses that use AI (58%) and businesses that do not (25%). After that, the top impacts are generating cost/budget savings (25% overall; 32% for AI users and 11% for non-AI users), followed by expanding their business (21% for AI users, 7% for non-AI users).

As outlined in Figure 10, small businesses that use AI see higher increases in their productivity and revenue growth as a result of adopting technology, even when the new technology being adopted is not AI.

Combining small businesses that do and do not use AI shows that the overall impact of non-AI technology on businesses that have adopted it in the last 12 months is an average of a five per cent increase in productivity, and a two per cent increase in revenue.

Before exploring these trends, it is interesting to reflect on the extent motivations for small businesses in adopting new technologies correlate with their actual gains.

A total of 74 per cent of those that adopted technology did so to work more efficiently. As Figures 8 and 9 demonstrate, this is somewhat borne out, but not to the level many might expect. Expectations were more likely to align with outcomes for users of AI, 86 per cent of whom adopted technology to work more efficiently, compared to 54 per cent of non-AI users.

Meanwhile, 31 per cent of small businesses implemented technology to provide cost/budget savings, and 25 per cent saw these savings. Expectations align with reality for a similar proportion of AI- and non-AI users alike.

Gap between productivity and revenue gains

Productivity gains as the result of adopting technology are more common than revenue gains across all groups analysed, for both AI and nonAI technology. In some sectors, this may reflect increased outputs in order to be competitive. For example, where AI is used in information and communication to support coding, quantity and/ or quality of their work may have increased, but lock-stepped competition means that those savings are passed onto consumers rather than resulting exclusively in higher revenue.

Productivity is measured as output per worker. Reduced staffing levels being offset by increased automation may also contribute to reduced costs without increasing revenue. Previous FSB research found that 24 per cent of small employers would respond to the UK Government’s Employment Rights Bill (now the Employment Rights Act 2025) by automating jobs.6 Our survey shows that this is playing out in practice. Eight per cent of small businesses were able to reduce staff levels as the result of introducing technology. Use of AI is a particular contributor, with 10 per cent of businesses that use AI having reduced their staff relative to four per cent of those that do not use AI.

10: Comparison of productivity and revenue impacts due to tech adoption, last 12 months

Source: FSB AI & tech adoption survey, November 20257

Figure

Qualitative research with small businesses shows that, where they have been able to automate jobs, this is often done alongside upskilling existing staff to help them move into adjusted roles. These roles often include more creativity, strategy or engagement with clients - in short, more ‘human’ qualities. Reductions in overall staffing levels are primarily due to businesses choosing not to recruit when someone leaves, rather than removing existing staff.

“Until recently it was myself and my husband who did all the core business marketing was around one tenth of my role. I’ve recently been able to start handing some of that to our employee, who’s very sharp and capable, but has dyslexia and can struggle with spelling and grammar. She uses a chatbot to help her get the grammatical bits right, and thanks to her great product knowledge she’s able to assist with marketing tasks now. This will enable us to expand her role, giving her more confidence, and it will free me up to focus on growing the business.”

Sarah Saunders, Black Shuck Distillery, East of England

Non-AI technology produces greater benefits for AI users than non-AI users

Businesses that take a more digital-first approach are likely to have been earlier adopters of AI, and also to have a better sense of how to use non-AI technology in the most beneficial way for their business. This selection bias in firms that are already using AI is therefore likely to be a factor in AI users seeing greater impacts from non-AI tech than businesses that do not use AI.

AI may also be helping small businesses to identify where recombination of existing knowledge or tools in new ways could provide benefits to a business. This is the principle underlying Agrawal, McHale and Oettl’s 2019 work.8 On the other hand, businesses that have adopted AI may be more likely to have overhauled their wider business processes and approach, in line with the tech adoption approach

advocated by Brunel University of London’s Professor Ashley Braganza:

“When it comes to adopting AI tech, you can’t just tinker at the edges. You’re not going to see much change if you do that. For the strongest, longer-term benefits, you need to step back and think, ‘What will be the environment we’re operating in? What are the challenges and opportunities we will face in the future? What are we trying to achieve?”

Professor Ashley Braganza, Chair in Organisational Transformation, Brunel Business School

Figure 11 indicates that the net positive impact AI adoption has on businesses’ level of revenue and productivity depends on whether it is used for more basic, efficiency-saving applications, or for more advanced applications focused on innovation or revenue-raising activities. Figure 11: Comparison of productivity and revenue impacts due to AI adoption, last 12 months

Source: FSB AI & tech adoption survey, November 2025

Those using AI for more efficiency and administration-related tasks, such as drafting written content and helping with emails, see a resulting 10 per cent productivity gains and 3 per cent revenue gains. Those using AI for more advanced, innovationfocused tasks like developing new products and services see higher productivity gains of 13 per cent, and revenue gains of 5 per cent.

How AI is used

Small businesses that use AI for marketing see equivalent productivity and revenue gains to those that use it for more advanced, innovation-focused tasks, reflecting Siedschlag and Duran’s findings from a study on businesses in Ireland.9

The productivity J-curve and delayed impacts of technology adoption

The productivity and revenue impact data analysed here relates to technology adopted in the previous 12 months. Impacts shown in these data points are therefore only relatively short-term. Indeed, 68 per cent of small businesses that have adopted AI in the last 12 months have not yet seen any resulting revenue change.

Greater up-front investment in adoption of technology may mean that immediate positive impacts on a business’ performance is lower than expected, although this may pick up over time as businesses’ use of adopted technology matures. This reflects the ‘productivity J-curve’, noted by Brynjolfsson in relation to the adoption of general purpose technologies (GPTs).10

“When a business brings AI in, they often see an initial dip in performance. But that’s not surprising - you need capital, patience to manage the change internally, and to upskill right across the organisation. Those who get the most out of AI do win big, but they also think about it deeply.”

Elizabeth Osta, Founder, Digital Forward LTD, London

Studies such as Siedschlag and Duran’s have found that the fast initial impacts of AI adoption on businesses diminish fairly quickly, whereas certain more innovative applications can result in longerterm impacts.11 Research by Sytsma suggests that this broader innovation of business processes and approach is one of three factors that determines the impact of a new technology on a business,12 alongside labour quality and investment in the tech itself. It is likely that businesses that invest in overhauling their wider business processes to align with the opportunities and challenges presented by

AI, with a particular focus on evolving their processes and approach rather than simply integrating AI into existing business processes, will see greater longterm payoffs.

Non-AI technologies and performance

Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and data analytics software are the non-AI technologies most closely associated with improved performance. This is strongest for ERPs, although this represents only 6 per cent of the small business population and is a technology concentrated in just a few sectors.

Small businesses who adopted ERPs were more likely than average to have generated cost/budget savings as a result of adopting technology (42% relative to 25% average for those adopting any form of technology) and to have reduced their workload (60% / 46%). They also show higher than average rates of business expansion and investment:

• 36 per cent having been able to expand their business in the UK (relative to 16% on average for tech adopters);

• 40 per cent having invested in new technology (15% average);

• 25 per cent having invested in staff training/ upskilling (9% average).

CRM and data analytics each also showed positive associations with some of these benefits, with 60 per cent of CRM-users able to reduce their workload and 37 per cent able to expand their business in the UK, and 25 per cent of data analytics users able to expand their business within the UK.

The impact for different types of businesses

Spend and business size

The more money small businesses spend on technology, the higher the benefits they see in terms of productivity and revenue gain.

Productivity impacts of non-AI technology are less closely associated with spend. Interestingly, while the self-employed appear to spend more

per head than employers, their returns are similar to micro businesses. Both of the self-employed and micro businesses that have implemented technology in the last 12 months are most likely to have spent between £1 and £1,000 (38% and 48% respectively). Both see similar productivity and revenue gains.

12: Comparison of productivity and revenue impacts due to tech adoption by business size and spend for the last 12 monnths

Source: FSB AI & tech adoption survey, November 2025

£1,001 to £10,000 on tech in last 12 months

Sectors

Figure 13: Comparison of productivity and revenue impacts due to tech adoption by business sector for the last twelve months

Source: FSB AI & tech adoption survey, November 2025

Figure

Sectors with higher AI adoption rates generally see greater returns from technology. 74 per cent of small information and communication businesses use AI, well above the 57 per cent average. For professional, scientific and technical services AI adoption also sits at 74 per cent. Figure 13 shows this sector has slightly above average productivity gains from AI, the revenue gains are the same as the average.

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Both of the sectors discussed above were also earlier adopters of AI, with adoption rates of 34 per cent and 37 per cent respectively in September 2023. For small businesses that adopted AI earlier, the use of this technology within these businesses is likely to have matured over this two-year period. Existing use cases can also demonstrate value in adoption, incentivising others in a given sector to invest in using AI within their business.

The Department for Business, Innovation, Science & Trade should:

• Introduce a Code of Practice to support employers to engage with their staff when introducing new technologies such as AI. Small businesses that have seen an increase in revenue as a result of implementing AI are more than twice as likely to have gathered ideas and feedback from employees than small businesses on average (36% compared to 17%). The Code should be non-statutory and should have advice tailored to employers of varying sizes which are likely to have varying needs and capacities.

• Set the Low Pay Commission (LPC) the explicit remit of examining the impact that National Minimum Wage/National Living Wage increases have on levels of automation and on the labour market, particularly the recruitment into lower-paid jobs. These insights should feed into the work of the AI Economics Institute regarding the impact of AI on the labour market. The LPC is currently required to consider the condition of the labour market, the cost of living, the impact on businesses and competitiveness, as well as wider macroeconomic conditions. Additional consideration should be given specifically to whether AI replacing jobs has been a consequence of higher National Minimum Wage/National Living Wage.

The Chartered Institute for IT should:

• Introduce an accreditation scheme for software integrators. Of small businesses that adopted technology in the last 12 months, one in seven (15%) of those that outsourced development or integration said that finding a reliable business to help integrate new software into their business is a barrier to adoption. Reliable accreditation would help provide certainty to small business consumers that a given service-provider will meet expected standards. This would also help those providing highquality services to differentiate themselves in the market. Requirements for accreditation should scale with integrator size, so that this does not become an outsized burden on smaller firms.

Chapter 3 - Moving beyond ‘adoption’: Concerns and opportunities for AI

As seen earlier in this report, many small firms are recognising both the threats and opportunities presented by AI and using it in exciting new ways. However, small businesses rarely have in-house legal expertise and often lack the resources to pay for it externally. In uncertain regulatory environments,

Concerns

this leads to a cautious approach to adoption, and overcompliance. Almost all the top concerns around AI could be linked to regulation, with around six in ten small businesses calling for greater AI regulation and four in ten saying it could give them confidence to invest in the technology.

Figure 14: Small businesses concerns about AI, comparing those who use AI with those who don’t

Source: FSB AI & tech adoption survey, November 2025

Inaccurate responses from AI tools

Abuse of my IP rights

AI-enabled crime

I do not trust AI providers to act responsibly with my data

AI security

My online content being used to train AI models

Lack of transparency about how AI models are trained

Environmental impact of AI

Exposure to legal liability or risk

Impact of deep fakes on my business brand / reputation

Uncertainty about implementing legally / ethically / responsibly

Lack of knowledge as to how AI can beneﬁt my business

Impact on business environment

Skills gaps

Long-term viability of my business

Identifying qualiﬁed candidates in recruitment

Other, please specify

know

As Figure 14 demonstrates, only a tiny number of small businesses have no concerns about the technology. Those small businesses currently using AI are more likely to be concerned by AI producing inaccurate responses (e.g. hallucinations). There are, however, several concerns that are felt considerably more among those that do not currently use AI, mostly related to AI providers and the misuse of the technology.

These was no notable difference between businesses using and not using AI regarding concerns that relate to impacts of AI on a business regardless of their own use. For example, concern about their online content being used to train AI models was felt by 35 per cent of AI- and non-AI users alike.

Despite being no more likely than average to say that they have concerns about AI in relation to their business (93%), disabled entrepreneurs are more likely than their peers who are not disabled to be concerned about their ability to manage AI securely (47% / 37%) and potential exposure to legal liability and risk (37% / 28%), as well as being more concerned about the impact of deepfakes on their business brand/reputation (39% / 29%).

Qualitative research with small businesses highlighted concerns across sectors and AI uselevels about how the data shared with AI models is handled. Particular concerns arose over transparency about where their input data is stored, what legal jurisdiction this data is governed by, how (if at all) their data is used to train future AI models, and the extent to which input data may be retrievable by other users of that AI tool. Concerns over how secure AI model providers’ data storage systems are was also a key concern for those using AI in more sensitive contexts.

Concerns likely to act as a direct barrier to adopting AI, such as uncertainty about how to implement legally / ethically / responsibly and a lack of sufficient skills are felt similarly by those that do and do not use AI. This suggests that tackling concerns about legal, ethical and responsible adoption could not only support businesses to start using AI, it would allow those already using the technology to use it with greater breadth and confidence.

“We use AI a lot in our business, and I do my research – I look at the Ts & Cs, I look at the supply chains, and so on. The AI tool we pay for says it won’t use our data to train its models. But we have so much sensitive data, and as an industry we’re massively regulated, but we don’t have control over how the data we input is handled. We have to be really careful with how we use the tools.”

Biotech consultancy, South East England

“For organisations working with government, data assurance is critical. Yet in practice, it is becoming increasingly difficult to know exactly where data is stored, processed, replicated or backed up. Whether the issue is an external AI tool or a cloudbased service, the complexity of modern digital infrastructure makes it hard to give absolute assurance that data will remain within a defined jurisdiction or be handled according to a specific set of requirements.”

Patricia O’Hagan, FSB member, Tech sector, Northern Ireland

34 per cent of small businesses have concerns about the environmental impacts of AI. In qualitative research with FSB members, concerns were raised about energy and water usage of data centres used for training and hosting AI models. This was linked to both ethical use of AI, and the impacts of data centres on local energy and water supplies for areas that host them. As highlighted by the Department for Energy Security and Net Zero in December 2025, ‘self-build options’ are being explored for data centre developers to contribute to energy supplies.13

“One thing I’m really concerned about is the environmental impact, and how sustainable or ethical it is for our business to be using AI when we know the environmental costs can be huge.”

FSB member, Fireriskassessments.com, East Midlands

Mitigating the risks from AI

Figure 15: Small businesses’ views on how to reduce the risks from AI

Source: FSB AI & tech adoption survey, November 2025

Regulation targeted at large tech ﬁrms

Protection for businesses using AI

Use case-based regulation

Sector-speciﬁc regulation

Use case-based Government guidance / support

Sector-speciﬁc private sector guidance / support

Sector-speciﬁc government guidance / support

Private sector support for speciﬁc AI uses

None of the above

Small businesses that use AI are more likely to identify a potential mitigation to the risks it presents (85%) than those that do not (75%). As Figure 15 demonstrates, the most-cited intervention was

regulation targeted at large tech firms (46%), which held for both businesses that use AI (49%) and those that do not (41%).

Figure 16: Small businesses views on how to reduce the risks from AI (summary)

Source: FSB AI & tech adoption survey, November 2025

Use car-based support Regulation

Sector-speciﬁc guidance / support

Confident AI adoption

‘Confident’ adoption could be the key to helping those that already use AI to use it better, and those that do not to use it at all. Interventions based on data protection, IP and regulation are cited as the top solutions by small businesses.

For small businesses that currently use AI, the top measures that would help them adopt AI more confidently are: assurance that AI adheres to data protection or copyright rules (51%), clarity over who owns AI outputs (44%) and clear labelling or watermarking of AI-generated content (43%). For small businesses that do not currently use AI, the top measures are more regulation of AI (37%), greater confidence that AI adheres to data protection and copyright rules (33%), and clear labelling or watermarking of AI generated content (32%).

40 per cent of small businesses say that more regulation of AI would help them adopt AI confidently, two thirds the proportion that said regulation of AI would mitigate the risks it presents in relation to their business (59%). This suggests that a lack of appropriate regulation is acting as a barrier to adoption of AI, as well as impacting small businesses’ experiences of the markets in which they operate regardless of whether they themselves use AI.

Knowing where liability sits in the AI supply chain is shown to be most impactful for the selfemployed (35%), declining with business size to 28 per cent for micro businesses and 27 per cent for small businesses. This may reflect the fact that the smallest organisations usually have the fewest resources to rely on when something does go wrong.

Figure 17: Small businesses views on what would enable them to adopt AI confidently

Source: FSB AI & tech adoption survey, November 2025

Knowing AI adheres to data protection or copyright rules

More regulation of AI

Labelling or watermarking of AI-generated content

Clarity over who owns AI outputs

Notiﬁcation of how business's data is used by a model

Support to adopt AI legally / ethically / responsibly

Knowing where liability sits in AI supply chains

Better access to AI assurance

Government-provided training grants

Government guidance / support to choose AI tools

Tax incentives for expenditure on training

Private sector support to choose AI tools

Support from peer networks

Other, please specify

Don’t know

None of the above

Confident adoption by AI use case

For those using AI for innovation-focused purposes, IP-related interventions would help them to adopt AI confidently. Those using AI to develop new products or services are notably more likely than average to say that clear labelling or watermarking of AI-generated content would help them adopt AI more confidently (50% relative to 38% for small businesses on average). They were also more likely to value clarity over who owns AI outputs (53% relative to 38% of all), alongside those using AI to identify AI-generated content (59%) and to edit or generate images (48%).

Knowing where liability sits in AI supply chains was more likely than average to be cited by those using AI for more advanced use cases (40% relative to 30% average). Better access to AI assurance processes to measure, evaluate and communicate the trustworthiness of AI systems was more likely than average (26%) to be cited by those using AI to help generate ideas (37%), to edit or draft emails (37%), and those that use AI to develop new products or services (40%).

Intellectual Property (IP) in an AI age

Supporting small business adoption of AI means building trust in the technology. Small firms have concerns about how AI models are trained and how their inputs are treated. 38 per cent are concerned about a lack of transparency about how AI models are trained, 35 per cent concerned about their online content being used to train AI models, 48 per cent don’t trust AI providers to act responsibly with their data, and 39 per cent are concerned about abuse of their IP rights. How AI outputs can be used against their businesses is also an area of concern, with 31 per cent concerned about the impact of deepfakes on their brand or reputation.

“My business designs and creates prints and embroidery for clothing, things like bags and T-shirts. I’ve always been really careful about IP. We started experimenting a bit with using AI for the design stage, but I quickly realised that we don’t know who owns what’s created. The grey area legally and general lack of clarity on the subject regarding this has put us off and that’s before we even think about whether what’s created might infringe on another artist’s copyright.”

Nikki Kirkland, Sew Ho Studios,

Scotland

Clarity over ownership of AI outputs is a potential opportunity for improvement, with 38 per cent of small businesses saying that clarity over who owns AI outputs would help them to adopt AI confidently. Qualitative research with FSB members shows that this is holding small businesses back from using AI for tasks that can be heavily assisted by generative AI, such as marketing, as well as limiting the extent to which creatives feel able to use generative AI in their work.

The UK Government response to its AI and copyright consultation, which closed in February 2025, set out measures focused on four areas: digital replicas (deepfakes), AI content labelling, control and transparency for creators, and licensing for independent creatives.14 The focus of the response was welcome and reflects themes of previous FSB research, with the potential to address the small businesses’ concerns about AI discussed above.

Indeed, FSB’s Creating Change report in November 2025 highlighted that voice and image rights are vital to protect creators from deepfakes and suggested that the Government should create a new and exclusive IP right to the voice and/or image of an individual, to prevent their exploitation by others for commercial or criminal purposes through the use of deepfakes.15 Similarly, in Creating Change (2025) and Redefining Intelligence (2024), FSB highlighted

the role of watermarks and disclaimers for AIgenerated content in being able to identify and value human creativity.16

Open standards like the Coalition for Content Provenance and Authenticity (C2PA)’s Content Credentials have shown the technical feasibility of creating a standard that ensure content that passes through AI models reflects some of that content’s history.17 C2PA’s standard includes finger-printing, a ‘coded representation of the content that can enable locating the original material and its associated Content Credentials.’ This standard has the benefit of being ‘tamper-evident’, such that machine-readable evidence will be available if a content’s history has been altered (even if the nature of the alterations cannot be determined). Labelling of AI-generated content is going to become mandatory in the EU in August 2026 under the EU AI Act.

Meaningful AI content labelling that allowed AIgenerated content to reflect the extent to which it is AI-generated, and the different AI tools used in its creation, could fulfil a number of functions. It could help tackle mis- and dis-information, allow creators to distinguish their work while not losing out on the benefits of AI, protect small businesses from commercially-damaging misrepresentation, signal to AI companies which content is already AI-generated to help them prevent model collapse,18 and help prevent erroneous labelling of content as AI-generated in a way that can damage creators’ credibility.

Legal, ethical and responsible adoption is particularly important for AI users

A notable proportion of both AI and non-AI users said that support to ensure they were able to adopt AI legally / ethically / responsibly would help them to adopt AI more confidently, cited by 31 per cent of small businesses, 39 per cent of AI users and 19 per cent of non-AI users. Similarly, while an average of 26 per cent said that better access to AI assurance (processes to measure, evaluate and communicate the trustworthiness of AI systems) would help them to adopt AI confidently, this was higher for users of AI than their non-AI-using peers (32% relative to 17%).

Legal liability for AI-related harms

Models for civil liability with regard to harms caused by AI are unclear, with contractual terms for AI use redistributing liability lower down the value chain towards small business users, as noted by the Ada Lovelace Institute in their report Risky Business.19 Small firms are therefore understandably concerned about security and legal use of AI, as well as the potential for legal liability to fall on them if something goes wrong with an AI model used by them.

AI models can act in unexpected ways, and are often opaque in their decision-making (known as the ‘black box’ problem). The potential harms from these systems are also varied, not limited to safety impacts such as making biased judgements based on skewed training data,20 and security challenges including revealing sensitive information shared with a model through prompt injection attacks.21

We see this reflected closely in small businesses’ concerns about using AI. 39 per cent of small businesses have concerns about security in relation to AI, 30 per cent about exposure to legal liability, and 27 per cent about adopting AI ethically, legally and responsibly. However, it is clear that small businesses are nevertheless choosing to use AI. This presents challenges for small firms, many of whom will have limited technical and legal capacity to make informed judgements about the tools that best-suit their business’ needs, the potential liability involved,

and how to mitigate any risks and accompanying liability. Small firms often over-comply with perceived regulation or best practice due to limited legal resources, which in the context of AI will limit the benefits their businesses are able to see from the technology.

Understanding the risks of using different AI models is made even more challenging by the limited information that large AI developers tend to share about the models they provide, including around serious safety and security incidents. Wider reporting of harmful cybersecurity incidents to regulators is likely to be required by the Cyber Security and Resilience Bill for operators of essential services and some managed and digital service providers, but reporting of many incidents remains voluntary for even the largest and most widereaching AI developers.22 If developers of large AI models were to share more information about their models with downstream developers and other business users of their models, this could help those firms to make better informed judgements about where and how they use those models, as well as providing supportive information for small firms that need to seek redress where those models have a negative impact on their business or customers.

There is some preference for use case regulation over sector-specific regulation, but the strongest preference is for upstream regulation of large tech firms, with 46 per cent of small businesses saying that regulation targeted at large tech firms would help mitigate the risks presented by AI in relation to their business (see Figure 15). Weighting regulation at this group would place the burden of compliance on those with the greatest reach across the UK economy, and with the resources to bear it.

Open source models and legal liability

Open source models provide potential for smaller firms to tailor models to suit their needs (or outsource this), as well as the potential to run AI systems locally in order to address security and data privacy concerns relating to cloud storage and sharing sensitive information with an AI model provider. Downstream developers’ ability to adjust models in ways that might affect their safety and security means that liability would usually sit less with the initial developer. A national body with responsibility for stewardship of the UK’s open source industry could help address these risks, while allowing small businesses access to free, locally-run and/or highly tailored models. Please see Chapter 7 for more on open source models.

Business choices and legal liability

Of course, in some contexts it is appropriate that legal liability links to how a business chooses to use AI. Sensitive use cases, such as in healthcare and financial services, require particular consideration. As the proportion of small firms concerned about adopting AI legally, ethically and responsibly shows, small businesses care about using AI in ways that do not harm their customers, their business, or their reputation. However, for many firms, working out how to do this will be challenging, and there is relatively minimal government support available to do so. Support for small firms to procure the best AI systems for their use case will be key, as will support to help small business owners to understand what best practice looks like in their own contexts. Examples of this will likely include what meaningful human oversight and ‘human-in-the-loop’ practices look like, how to develop evaluation and feedback loops for the use of AI within a business, and how to create a healthy culture of AI use, for those with employees or contractors.

Trusted AI certification could help tackle liability issues in supply chains

As outlined in Figure 14, 41 per cent of small businesses are concerned about AI-enabled crime, 39 per cent are concerned about their ability to manage the technology securely, and 30 per cent are concerned about exposure to potential legal liability or risk. The approach of the National Centre for Cyber Security’s Cyber Essentials has some value as

a model for supporting small businesses to adopt AI safely, securely and ethically.

FSB members who have achieved Cyber Essentials accreditation have given the programme positive feedback, especially regarding the Cyber Liability Insurance. The scheme provides certification of cyber security following a self-assessment and independent audit.23 Accredited businesses benefit from Cyber Liability Insurance provided by the programme’s delivery partner IASME.24 The more advanced Cyber Essentials Plus certification is also available, at higher cost.

“The insurance you get when you complete Cyber Essentials is great - I’ve never had to use it, but it gives me real confidence and peace of mind. Something like that for AI would really help me use AI more, and know that if anything goes wrong, my business will survive.”

Heather Spencer, AdminWorks, South East England

Despite this, overall take up by small businesses remains low. In 2025, only three per cent of the small business population had Cyber Essentials certification.25 FSB member feedback consistently shows that cost is a barrier to initial certification, and a 2023 evaluation of Cyber Essentials found that challenges with cost and time were among the top three reasons for certifications lapsing.26 Cost is a particular challenge where significant technical work is required to bring a business’ systems up to the right level, which often requires out-sourcing.

Access to Cyber Essentials certification is becoming increasingly important for small businesses’ access to supply chains. The Government has required Cyber Essentials or Cyber Essentials Plus certifications for those bidding for some government contracts since 2014, or for suppliers to demonstrate similar technical controls.27 Following a number of high-profile cyber attacks in the UK in 2025, the UK Government has strongly encouraged businesses to use Cyber Essentials to shore up the cyber resilience of their supply chains, including through publishing a Cyber Essentials Supply Chain Handbook.28

While the focus on cyber resilience is welcome, the above-mentioned cost barriers to small business certification mean that additional supply chain requirements for Cyber Essentials certification risks locking small businesses out of these opportunities. A similar phenomenon can be seen with AI safety and security standards and accreditations, with some firms already requiring certain suppliers to align with the ISO/IEC 42001 standard for managing AI systems.29

If the government takes a similar approach to responsible small business AI adoption as it has to cyber security, then support must be provided lowor no-cost so that it acts as an enabler of confident small business AI adoption rather than a barrier. An affordable and technically feasible alternative to existing highly technical standards is also needed for businesses using AI in an ‘everyday’ way.

Concerns and remedies by sector

Concerns

Figure 18: Small businesses’ concerns about AI, substantial sectoral differences

Source: FSB AI & tech adoption survey, November 2025

Guidance and support

Small businesses in information and communication are less likely than average to opt for government guidance/support for specific use cases (17% relative to 26% average), and also for more sector-specific private sector guidance/support (15% relative to 24% average).

Professional, scientific and technical small businesses are more likely to cite more sectorspecific private sector guidance/support (35%) and more protection for businesses using AI (54% relative to 42% average). It is unsurprising that those in professional services are more desirous of sectorspecific support, as this will include sectors like

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The UK Government should:

Financial Services and Legal in which professional standards are high and prescriptive. However, it is interesting that this need is not being met, given that Financial Services has been a focus for sectorspecific AI guidance from the Financial Conduct Authority (see their briefing in September 202530 and their AI regulatory sandbox, the AI Lab31). It may reflect low awareness of regulatory sandboxes. More broadly, this reflects similar concerns to those raised in the Treasury Committee that the sector’s use of AI is exposing the UK’s financial system to an unnecessary level of risk.32

• Place the Digital Regulation Cooperation Forum (DRCF) on a statutory footing with responsibility for maintaining a co-ordinated approach to AI regulation and ensuring appropriate international interoperability. Having a single body with statutory accountability for AI regulation would allow for a more agile, coordinated approach, and put the UK in a position to make the most of new technologies as they arise. The Forum should be given enhanced powers and resources in order to meet evolving challenges from regulating technology. An independent chair should be established with direct accountability to Parliament, and relationships of DRCF regulators should be formalised through measures such as duties to consult and statutory information-sharing mechanisms, as proposed in the House of Lords Communication and Digital Committee’s report, Digital regulation: joined-up and accountable 33 The DRCF should also become the first port of call for reporting new or suspected risks with AI, without fear of enforcement.

• Build a ‘Responsible AI Essentials’ programme modelled on the National Cyber Security Centre’s Cyber Essentials. A total of 39 per cent of small businesses have concerns about being able to manage AI securely, and 30 per cent about exposure to legal liability or risk. The programme should include key features of Cyber Essentials, such as self-assessment with an independent audit, with accompanying AI Liability Insurance. Certification should be low- or no-cost, with financial support for implementation available through responsible AI adoption vouchers.

• Introduce responsible AI adoption vouchers to help small businesses achieve Responsible AI Essentials certification. FSB member feedback consistently shows that cost is a barrier to initial Cyber Essentials certification, and a 2023 evaluation of Cyber Essentials found that challenges with cost and time were among the top three reasons for certifications lapsing.34 Cost is a particular challenge where significant technical work is required to bring a business’ systems up to the right level, which often requires out-sourcing. In addition to introducing a parallel programme for AI adoption, Responsible AI Essentials, the UK Government should introduce vouchers for the smallest firms to receive support to implement the technical changes required to achieve certification. Vouchers should start at £500 for the self-employed, rising to a maximum of £5,000 per small business (a third of the value of BridgeAI’s

Innovation Vouchers for AI adoption). Vouchers should be limited to spending with governmentassured Responsible AI Advisors, this scheme’s equivalent to Cyber Advisors, and on activities required to achieve certification.

• Continue to build out the AI Skills Hub with a focus on clear and transparent credentials for users, so a user can track on their profile their level of development against each of the core skills. This should have both employer and individual versions, so that employers are supported to build workforce development plans for their entire workforce. This could be embedded in a digital tools and skills diagnostics tool, which would in turn feed users through to the Hub and help it reach small businesses.

• Introduce upstream regulation of large tech firms, requiring them to mitigate risks presented by AI in relation to its use in business contexts. 30 per cent of small businesses have concerns about legal liability in relation to AI, and 46 per cent of say that regulation targeted at large tech firms would help reduce the risks from AI. This regulation should help promote transparency and information sharing, and would require that liabilities are passed downstream only where appropriate and as proportionate. Information should be made available to prospective and existing users, to help small firms make considered judgements about the best tools for their purposes and to provide evidence if they need to seek redress for AI-linked harms. This should include provision for civil liability for large tech firms that provide assurances that small businesses rely on to their detriment.

• Develop a responsible AI adoption course for small business owners that is government-funded and endorsed. This would be hosted on the AI Skills Hub, so that small businesses are equipped to take a responsible approach to AI adoption. It would help small business owners to understand legal and ethical considerations to using AI, and give them the skills to choose between different AI tools based on their sector, use case and risk appetite. This should be exclusively government-funded so small firms can have confidence in its objectivity. Small business-specific aspects could be included as a module within a wider course on responsible AI use for UK workers and citizens, with the wider course taking a similar approach to the University of Helsinki and MinnaLearn’s widely-used Elements of AI course.35 This could sit alongside additional AI procurement support, providing a private sector equivalent to the Government Digital Service’s Guidelines for AI Procurement 36

• Mandate AI content labels for large AI developers and online platforms. 31 per cent of small businesses have concerns about the impact of AI deepfakes on their brand or reputation. Content labels would protect small firms from fraudulent misrepresentation, tackle mis- and dis-information, and help small creators to make use of AI while demonstrating their own creativity. This would create a machinereadable history for a piece of content that has gone through AI, reflecting the proportion of the content that is AI-generated and also which AI tools were used. This could build on the work of existing open standards such as the Coalition for Content Provenance and Authenticity (C2PA)’s Content Credentials.37 Labels could be visually presented as a percentage, showing the extent to which a piece of content is human created.

• Introduce an obligation on providers of the largest foundation models to document and report serious safety and security incidents, as well as a requirement to ensure an adequate level of cybersecurity protection. For example, in line with the Code of Practice for the Cyber Security of AI, which sets out a minimum standard of cyber security in relation to AI and the necessity of developers establishing audit trails for AI models.38 This should be enforced by the Digital Regulation Cooperation

Forum (DRCF).

• Give the Intellectual Property Office powers to proactively investigate large-scale breaches of copyright in relation to AI and deliver regulatory enforcement. The Digital Regulation Cooperation Forum (DRCF) should be given powers to direct the IPO to launch investigations, and to take enforcement action where necessary. This would allow the IPO to effectively enforce copyright laws to protect the output of authors, creators, and other publishers from misappropriation and misuse from AI developers. Additionally, to establish a trustworthy and transparent system for auditing the use of copyrighted material in AI systems. The IPO already has similar powers to enforce copyright with regard to licensing bodies.39 There should be a route for small businesses to report suspected infringements directly to the DRCF, such as a phoneline and online form.

The Digital Regulation Cooperation Forum, led by the Information Commissioner’s Office, should:

• Publish a set of ‘AI model cards’ with key information about the most widely-used AI tools. 48 per cent of small business owners are concerned about AI model providers acting responsibly with their data. Model cards should build trust by transparently reflecting where input data is stored (jurisdiction), how the model provider commits to using this data, measures taken to prevent IP infringement in outputs, where liability lies if something goes wrong, and whether users own the outputs. The ICO should be given powers to require this information to be shared with them by the relevant AI model providers, so that cards reflect only the information shared with them directly. This data should be required to be available within any widely-used AI tool, such as with a banner or ‘model card’ button visible to users at all times.

The Intellectual Property Office should:

• Create a new and exclusive IP right to the voice and/or image of an individual, to prevent their exploitation by others for commercial or criminal purposes through the use of deepfakes. This could also include defining such usage as an ‘unfair business practice’ carrying a compensation right, in the same way as many unfair practices are prohibited under UK law to protect consumers. This could build on work in some US states and Denmark, as recommended by the Foreign Affairs Committee.40

The Department for Business, Innovation, Science & Trade should:

• Introduce incentives for AI data centres to provide their own energy generation. 34 per cent of small businesses are concerned about the environmental impacts of AI, including the impacts of data centres on local electricity and water supplies. Those that supply at least 50 per cent of their energy needs could be exempted from certain policy costs, for example Renewables Obligation charges.

Local authorities should:

• Recognise the impact of data centre developments on local communities and focus associated Section 106 funding on mitigating negative impacts and supporting local small businesses to adopt technology. Under Section 106 of the Town and Country Planning Act 1990, developers can commit funding or other support for use by the relevant local authority as part of planning applications. This funding should be focused on mitigating negative impacts, such as on local water and energy supplies, and also on supporting small firms to make the most of technology.

Primes in supply chains should:

• If they decide to impose requirements for their suppliers to introduce specific technologies or build their cyber resilience measures, primes should use their resources to provide advice and support to small businesses in their supply chains.

Chapter 4 - Practical interventions for successful adoption

For small businesses considering adopting or updating their technology, the key questions are: what do I do, how much will it cost, and where do I start? While cost is a factor, the key barrier – and enabler – to small business tech adoption is simply knowing what to do and how to do it. As Chapter 2 shows, those that are using AI in revenue-raising

ways are seeing greater returns from technology. To maximise economic impact, government support for small business tech adoption must focus not on maximising the number of firms that use digital technologies, but on helping them use tech in the best ways for their businesses.

Barriers and incentives for technology adoption

Source: FSB AI & tech adoption survey, November 2025

I cannot decide whether it is worth the effort

Lack of time

Lack of know-how in implementation

Concern that the technology will not meet expectations

The cost is too high or uncertain

Concern about complying with regulation

I don't know where to start

Lack of suitably skilled staff

Lack of suitable way to ﬁnance

Poor mobile data or internet connection

Concern about accessing relevant business data

I am worried it will be too big a change for my business

I cannot ﬁnd a reliable software integrator

Don’t know

Figure 19: Barriers for small businesses adopting new technologies

Figure 20: Incentives for small businesses to update or adopt new technologies

Source: FSB AI & tech adoption survey, November 2025

Better information and guidance on how to implement

More awareness of the potential beneﬁts

More capacity (time) to successfully implement

Increased tax relief / credits

More government grants that I can apply for

More support to help implement

Better internet connection

More suitably skilled staff

Comparison with early 2023

In FSB’s 2023 report The Tech Tonic, we found that the top barriers to innovation are a lack of time (40%), cost being too high (28%), a lack of suitably skilled staff (22%), and being unable to decide whether innovation is worth the effort (22%).41 Lack of time, cost challenges, and uncertainties around the returns on investment continue to be top concerns, but we see that those citing lack of suitably skilled staff as a barrier has declined from 22 per cent to 15 per cent, lack of know-how in implementation is a more significant barrier, having risen from 17 per cent to 29 per cent. This corresponds with 31 per cent saying that support to adopt legally / ethically / responsibly would help them to adopt AI confidently.

“When people come to us looking to use tech, it’s not really about the technology. It’s about the people. We always start with active listening. We may end up helping them identify a couple of tools that could really work for them, or even building them something bespoke, but it won’t be any use unless it’s solving a problem or helping them make the most of an opportunity.”

Patrick

Kelly-Weller, Adapt Digital Ltd, London

Comparison of incentives tell a similar story. However, while the top incentives for business innovation in the widest sense in 2023 were focused on financial cost (government grants cited by 50% and tax reliefs/credits by 34%), when looking at those considering innovating their business processes the focus was more on time and uncertainty in implementation. Support to help implement was cited by half (50%) of this group as an incentive, followed by access to better information, advice and guidance (42%) and more capacity to implement (37%). When compared with the survey for this report, the barriers to small businesses innovating their processes remain much the same, with some decline in relevance in access to suitably skilled staff. There is, however, a renewed focus on business owners’ understanding of why and how to successfully implement technology in an uncertain regulatory environment and when the pace of change in the technology itself is high.

“The technology we have now is vastly different to what we had even six months ago. We had been

exploring apps and none of

them could quite do what we

needed,

but we’re now seeing new options come out every day. It’s exciting.”

Ruth Partington, Owner & Founder, Empower Translate, Wales

Business location and connectivity

There is an urban/rural divide in connectivity, but this is perhaps not as dramatic as might be expected. While six per cent of urban-based businesses cite poor mobile data or internet connection as a barrier to adopting new technologies, those based rurally are markedly more likely to cite this at 15 per cent.

This perhaps affects the range of technologies available to businesses, shown in the gap in usage of cloud computing between urban- and rurallybased businesses (51% / 43%). FSB data collected in December 2025 showed that of the small businesses affected by broadband problems, the top areas of their business affected were:

• access to cloud computing or online files (35%)

• customer communications (34%)

• internal business communications (29%)

• access to online banking (26%).

At the regional level, those in the East Midlands (22%) and West Midlands (18%) were more likely than those in London (9%) and Yorkshire and the Humber and the North East (6%) to say that better internet connection would help them adopt or update technology.

Slow broadband speed and other challenges relating to broadband, such as unreliable connection and poor customer support, all seem to be potential barriers to technology adoption.

A gap in government support for small business tech adoption

Innovate UK is often pointed to as a driver of innovation in the business community, including in the context of business process innovation and technology adoption. When the Technology Strategy Board came into UK Research and Innovation (UKRI) and became Innovate UK under the Higher Education and Research Act in 2017, it was expected that ‘Innovate UK [would] not just become the commercialisation arm of the Research Councils’, but its role within UKRI would hold responsibility ‘for helping drive productivity growth across the UK by supporting innovative organisations’. Innovate UK currently positions itself as ‘the UK’s innovation agency’.42

While much of Innovate UK’s work has focused on firms that are technology- or science-driven, some has also focused on dissemination of existing innovation among firms not necessarily considered ‘innovative’ themselves. For example, Innovate UK’s BridgeAI programme was established to promote AI adoption in sectors considered to have high potential: agrifood, construction, creative, and warehousing and logistics industries (since expanded to include other industrial strategy sectors).43 BridgeAI’s Year 3 report for 2025-26 shows the range of activities sponsored by BridgeAI.44 £74.6 million of the programme’s total of £100 million of funding has been issued in funding and grant competitions, focused largely on research and development, feasibility studies, establishing investor partnerships and tackling data sharing issues in supply chains. Measures focused more on delivering practical support to small businesses looking to adopt AI have been implemented on a fairly small scale, including Innovation Vouchers and Independent Scientific Advisors. Together with High Performance Computing Vouchers, providing £5,000 for access to a supercomputer, these programmes have delivered 90 vouchers and reached a further 252 participants. 69 per cent of those that accessed support from ISAs reported ‘measurable technical or organisational progress’, while between 60 and 70 per cent of

voucher recipients noted ‘reduced costs, increased productivity, and/or improved efficiency’. These programmes seem potentially promising as models for wider-scale AI adoption support, although they have only been delivered on a small scale and the impact data currently available is limited.

BridgeAI also built the AI Skills Hub, which highlights a range of AI skills courses. The accompanying AI Skills Boost Initiative was announced in June 2025, with an ambition to upskill seven million UK workers by 2030, upgraded to 10 million in January 2026.45 FSB is an industry partner in the initiative.

While some of Innovate UK’s work has focused on diffusion of existing technology, as outlined above, decisions such as the cancellation of the successful Smart Grants programme (more in Chapter 7) suggest a shift in direction towards a more targeted approach. This aligns with statements from UKRI’s CEO, Sir Ian Chapman, to the Science, Innovation and Technology Select Committee on the 3rd February 2026. Talking about Innovate UK, Chapman said, ‘In the past, we have been guilty of investing in too many at too little… I would like us to be able to be more focused in how we choose the companies that are high-growth potential and then support them in a more concerted way.’46

FSB data shows that 20 per cent of small businesses struggle with knowing where to start when adopting technology (Figure 19). Innovate UK’s focus on a small set of firms with perceived ‘highgrowth potential’ risks leaving a gap in support for small businesses looking to adopt technology and innovate their business processes. The SME Digital Adoption Taskforce, of which FSB was a member, recommended in their final report that the Business Growth Service should have an explicit focus on digital adoption, with ‘a specific pillar, and advice, on technology selection, uptake, deployment and support’.47 This has yet to be put in place.

Regardless of delivery mechanism, there is a clear economic case for broad-based support for small

business technology adoption. As seen in Chapter 2 (Figure 10), small businesses that have adopted technology in the last 12 months have seen an average resulting increase in revenue of 3 per cent as a result. If the number of small businesses not using AI could be halved, and depth of use by current small business AI users could be increased by 50 per cent, this could add £42 billion to the UK economy each year.48 Given the complexity of the tech adoption support landscape, transparent delivery of support under one body would help ensure that the support reaches small businesses across sectors.

Tech adoption support across the devolved nations

The UK Government should also look to successful initiatives in the devolved nations for inspiration on how small businesses can be supported to meaningfully adopt new technology, particularly AI.

The Artificial Intelligence Collaboration Centre (AICC) is a £16.3 million initiative led by Ulster University and Queen’s University Belfast, focused on supporting AI adoption and ecosystem development in Northern Ireland.49 The initiative

delivers skills and wider AI adoption support, with an emphasis on responsible adoption and a specific stream to support small businesses (the Transformer Programme). Positive feedback from FSB members suggests that there may be merits to such fullyfunded, wrap-around support.

The Scottish Government have published their AI Strategy for Scotland, with focus areas including adoption and skills, companies and products, and regulation.50 It also emphasises areas of relative strength for Scotland, such as renewable energy sources for AI. As part of this, the Scottish Government have launched a programme to support small business adoption of AI, the AI Adoption Programme, with nearly £1 million in funding for the first iteration launched in 2025. Similar to support provided by the AICC, the AI Adoption Programme provides skills development and a focus on ethical adoption, in addition to consultancy services. The programme has been welcomed by some FSB members in Scotland as providing relatively helpful support, with the grant funding provided being especially useful.

Barriers and incentives for different business types and demographics

AI users

Small businesses that do not use AI are more likely than their peers to select barriers relating to initiating the technology adoption process. For example, businesses that do not use AI are six percentage points more likely to say that they cannot decide whether adopting technology is worth the effort (35% relative to 29%), and that they don’t know where to start (23% / 17%).

Small businesses that currently use AI, on the other hand, are more likely to cite barriers relating to expertise in the implementation process itself, such as a lack of know-how in implementation (32% of AI users relative to 25% of non-AI users). Turning to

incentives for adoption, businesses using AI consider barriers to adopting technology more tractable than those who do not use AI. 85 per cent of AI users list an incentive that would help them adopt or update technology, relative to 65 per cent of those that do not use AI.

Sectors

Those in construction were notably more likely than average to say that being unable to decide whether it is worth the effort is a barrier to adopting new technologies, at 41 per cent relative to an average of 32 per cent. There were few notable sectoral variations in incentives to adopt technology, which when taken alongside the above findings is

interesting in itself. Manufacturers were more likely to say that more suitably skilled staff would help them to adopt or update technology, cited by 20 per cent relative to an average of 10 per cent.

Variation by nations and regions

Better information and guidance on implementation was more likely to be cited by small businesses in the South West (41%) and East of England (40%), and less likely for those in the East Midlands (28%) and Yorkshire and the Humber and the North East (26%), relative to an average of 34 per cent. This may reflect regional and national differences in business support provision. Small businesses in Scotland were markedly more likely than their peers in England and Wales to say that more awareness of potential benefits would help them adopt or update technology (41%, relative to 33% and 31% respectively). On the other hand, those in Wales were more likely to say that they would be incentivised by increased tax reliefs/tax credits (41% relative to an average of 32%) and more government grants to apply for (49% relative to an average 30%), suggesting that financial cost is a particular barrier to tech adoption in Wales.

“The support you get varies so much depending on where you are and what your local innovation ecosystem looks like. Growth Hubs can be great, but they vary a lot in how knowledgeable they are on AI and how much focus they put on it. The patchiness of business support means it’s really just luck of the draw.”

Richard Askew, FSB member, Software business, North East England

Disabled

entrepreneurs

Qualitative feedback from members highlights how technology is helping disabled entrepreneurs to navigate complex business environments and work in ways that work for them. Even fairly basic, low-cost technology, such as audio reading within Word documents can make a big difference to small business owners with long-term health conditions.

“Something I’ve found really helpful is the read back function in Word. You used to have to pay for a special software, but now it’s all built in. It means I can just highlight a block of text and ‘read’ a document even when I can’t keep my eyes on the screen for long.”

Lorraine Stanley, Founder & CEO,

SWAD CIC

However, while disabled entrepreneurs are similarly likely to non-disabled entrepreneurs to say that they do not have any barriers (12% and 13% respectively), disabled entrepreneurs are substantially more likely to say that costs being too high or uncertain are a barrier (33% / 25%). Previous FSB research found that 11 per cent of disabled entrepreneurs or those with a long-term health condition have struggled to access the equipment they need.

This is seen among those who are just starting out, for whom having the right technology is key to being able to operate a business. Access to Work is a government-funded grant scheme, one function of which is to fund the purchase of equipment to support disabled people and those with long-term health conditions in the workplace. It does not cover reasonable adjustments, which employers are required to make for their disabled employees. Although self-employed people are eligible for the scheme, small business owners report challenges accessing the scheme when working to establish their business.

“They require you to have a business plan before they can evaluate you and suggest any gizmos, gadgets or humans that might be of help. So, my business was delayed by several years because I couldn’t afford the tech at the time.”

Lorraine Stanley, Founder & CEO, SWAD CIC

Implementing technology that is accessible for disabled customers can also be prohibitively expensive. One FSB member whose business serves disabled people highlighted the potential for AI to help with translating the business website into British Sign Language (BSL), which has a distinct syntax to spoken English and is a first language for some with hearing impairments. They noted that there is existing technology that facilitates on-demand translation of written English into BSL, with facility to patch through to a BSL interpreter to answer any questions.

“It’s great, a really clever little gizmo. The stuff we deal with is often really personal, so it’s important that we’re able to communicate with people in the way that’s easiest for them to understand and engage with. The real issue is the cost.”

Lorraine Stanley, Founder & CEO, SWAD CIC

Technology can support routes into work

It is notable that the previous Government’s Digital Inclusion Action Plan identifies five groups most at risk of digital exclusion: young people, older people, people with disabilities, people currently out of work and low-income households. This has some parallel with groups most likely to be economically inactive. For example, 13 per cent of young people (aged 16 to 24) were not in education, employment or training (NEET) in the third quarter of 2025.51 Disabled people are also less likely to be employed than their non-disabled counterparts, at 52.8 per cent relative to 82.5 per cent respectively.52 The dual factors of digital and economic exclusion for some of these groups present both a challenge and opportunity.

FSB data shows that self-employment can sometimes be a route into work for those that would otherwise not be able to, or choose to, take on a traditional job.53 FSB data shows that 18 per cent of small business owners set up their business as their personal circumstances were not compatible with a conventional job, a figure that rises to nearly a quarter (24%) for disabled entrepreneurs. This data also shows that 48 per cent of sole traders would value access to free or subsidised impartial business support advice. The New Enterprise Allowance, a government scheme that supported the self-employed who were receiving benefits to build their business, closed in 2021 despite strong evidence of its effectiveness at supporting older and disabled people into work.54 An updated version of this programme could be introduced with a focus on digital skills and wider business support. The programme would support those most at risk of digital exclusion to build digital-first businesses across sectors and could help support labour market participation.

RECOMMENDATIONS

The Department for Business, Innovation, Science & Trade:

• Develop a tech adoption and digital skills diagnostic tool, housed on the Business Growth Service website and linked with responsible AI adoption vouchers and the AI Skills Hub. This would provide small business owners with advice on what business processes they could potentially automate advice andsignposting to encourage them to do so. Within this tool, there could be an assessment of a company’s current and future digital skills needs and what training would help them and/or their employees. There should be a different track for the self-employed. This would then refer businesses through to additional support such as the AI Skills Hub where relevant. This could include an aspect of the CTO-as-a-service model rolled out in Singapore, recommended in AI format for scalability by the SME Digital Adoption Taskforce.55

The Department for Digital, Culture, Media & Sport should:

• Introduce grants for small businesses to make their services more accessible using technology. Advances in technology can provide opportunities for businesses to make their services more accessible to current and potential customers, but small businesses report that cost remains a significant barrier. Grants should be for up to £3,000 per business. Examples of how grants could be spent include British Sign Language (BSL) interpretations for online services and resources, engaging support to add a ‘calm mode’ toggle to websites to reduce stimulation for those for whom screen usage can trigger migraines, and formatting websites and other resources to be more visually accessible to people who are neurodivergent. The first round of the Digital Inclusion Innovation Fund focused on supporting innovative interventions and best practice for supporting digital inclusion in England, including for disabled people.56 This grant could be introduced as part of a future round of the Fund, to help small businesses put in place the insights from the first round.

Ofcom should:

• Work to extend protections already offered to microbusinesses to businesses with up to 50 employees, in relation to telecoms. Broadband contracts are fundamental to running a business in the modern economy, but small businesses have reported opaque contracting terms and mid-year bill rises. To ensure small and medium businesses aren’t unduly targeted in the sector, Ofcom should work at strengthening the small business protections provided under Part C of its General Conditions of Entitlement.57 This should include a ban on long-term contracts (over 24 months) and a ban on autorenewal contracts.

Local authorities and Business Improvement Districts (BIDs) should:

• Establish high streets-focused digital adoption programmes focused on basic digital adoption, with an additional ‘bricks and clicks’ strand to support high street retailers to establish or enhance their online offerings. The basic digital adoption programme would support high street businesses to develop and enhance their own websites, marketing strategies, and loyalty schemes. This initiative would help bridge the gap between traditional retail and the digital marketplace, so that small high street businesses can competitively and effectively engage in the evolving retail landscape. The structure of the programme could be modelled on the North West pilot of the Adoption stream of the Made Smarter tech adoption programme for small manufacturers, with specific support for technological, leadership and organisational/workforce development.58 Private sector experience and knowledge of business innovation should be essential criteria in the development of this new programme.

HM Treasury should:

• Introduce a ‘technology adoption and productivity tax relief scheme’ based on R&D tax credits for Corporation Tax. As shown above, if the number of small businesses not using AI could be halved, and depth of use by current small business AI users could be increased by 50 per cent, this could add £42 billion to the UK economy each year.59 This tax relief would provide financial support for small businesses that spend money on adopting technology to build their productivity, such as AI. This could be similar to the recommendation by the Business and Trade Committee in February 2026 for the Government to ‘bring forward proposals for tax incentives to encourage increased intangible investment and the diffusion of productivity enhancing general purpose technologies, such as artificial intelligence’.60 Small businesses should be entitled to claim a relief of 126 per cent, so that firms with profits below £50,000 a year on a Corporation Tax rate of 19 per cent pay five per cent less for qualifying expenditure.

The Department for Work and Pensions should:

• Introduce a New Trader Allowance for jobseekers, particularly for groups most at risk of digital exclusion such as disabled and young people, which would offer tailored support and increased payments to help them transition into entrepreneurship. The new scheme would focus on supporting those who are currently unemployed to take advantage of opportunities presented by technology to build digitally-enabled businesses across all sectors, from retail and construction to marketing. It would be a more effective and ambitious replacement for the New Enterprise Allowance (NEA), and should be available to all those not currently in employment. The scheme should provide tailored support for jobseekers, including on digital skills and wider business support.

Chapter 5 - A difference of approach: Female entrepreneurs

Female entrepreneurs are extremely innovative. FSB research in 2023 found that 76 per cent of female entrepreneurs had made innovative changes to their business in the last three years.61 This trend continues to be the case, with female small business owners slightly more likely to be using AI than their male counterparts. However, they also have

higher rates of concerns about AI, and are seeing lower productivity and revenue gains, likely due to taking a more cautious approach to implementing AI. Guardrails around AI use and support for legal, ethical and responsible adoption of AI are likely to be crucial measures for ensuring that female entrepreneurs are equipped to get the most from AI.

Female entrepreneurs’ use of AI

Female business owners are slightly more likely to use AI (59%) than their male counterparts (56%), although the difference is not great.

Differences in rates of use of AI are particularly substantial for use cases likely to involve off-theshelf generative AI, such as generating ideas (35%

for women / 25% for men); editing or drafting written content (30% / 22% for emails, 42% / 35% for other content); and creating marketing content (36% / 28%). Male business owners are also more likely than their female counterparts to use a proprietary or bespoke AI tool (5% / 2%), although there is no difference in use of sector-specific tools (both 5%).

Female entrepreneurs are seeing lower returns from tech

Figure 21 shows that female entrepreneurs have seen lower productivity gains and revenue gains than their male counterparts as a result of adopting AI.

There were no substantial differences in steps taken by female and male entrepreneurs to implement

technology, except that female entrepreneurs are slightly more likely to have developed an AI policy (11% / 7%) and less likely to have developed technology in-house (11% / 21%).

Figure 21: Comparison of productivity and revenue impacts due to AI adoption by gender

Source: FSB AI & tech adoption survey, November 2025

There are no noteworthy differences between the proportions of male and female entrepreneurs using AI for at least one of the more basic applications, or for those using AI for one of the more advanced applications. Female entrepreneurs were slightly more likely to use AI in both ways. 56 per cent of female entrepreneurs use AI for basic tasks and 43 per cent for more advanced tasks; in contrast 50 per cent of male entrepreneurs use AI for basic tasks and 38 per cent for more advanced tasks.

On the other hand, qualitative impacts of adopting technology suggest that male and female entrepreneurs are choosing to use the benefits of technology in different ways. This is likely a factor in female entrepreneurs seeing lower revenue gains

from tech than their male peers, although this does not explain why productivity gains are lower for female entrepreneurs. As the result of technologies adopted in the last 12 months, male entrepreneurs are more likely than their female counterparts to have generated cost / budget savings (26% / 20%), to have put savings back into the business to manage cash flow (14% / 7%), and to have invested in new technology (18% / 7%). They are also slightly more likely than their female counterparts to have reduced staff levels as the result of implementing technology (9% / 5%). Female entrepreneurs, on the other hand, are more likely to have reduced their workload (51% / 46%).

Depth of AI adoption by female entrepreneurs is limited

by their concerns

Female business owners are slightly more likely to have concerns about AI (95%) than their male counterparts (91%). For all concerns where there was a notable gender differential, women were more likely to cite that concern. These differences are particularly substantial for the following concerns:

• the impact of deepfakes on my brand / reputation (36% female / 28% male)

• lack of knowledge as to how AI can benefit their business (39% / 28%)

• uncertainty about how to implement AI legally / ethically / responsibly (34% / 24%)

• potential exposure to legal liability or risk (38% / 27%).

Source: FSB AI & tech adoption survey, November 2025

Regulation targeted at large tech ﬁrms

Use case-based regulation

Use case-based Government guidance / support

Private sector support for speciﬁc AI uses

Sector-speciﬁc regulation

Sector-speciﬁc government guidance / support

Sector-speciﬁc private sector guidance / support

for businesses using

Interestingly, these span all of the three broad categories of concerns: uncertainty and lack of knowledge act as barriers to adoption of AI, concerns about deepfakes stand regardless of a business’ use of AI, and potential legal liability or risks arising from a business’ use of AI.

When it comes to mitigating these risks, male business owners were overall more likely to favour regulation, while female entrepreneurs were more likely than their male counterparts to favour guidance, support, and protection for users of AI. This is outlined by Figure 22 below.

Figure 22: Small businesses views on how to reduce the risks from AI by gender

Support for confident adoption shows a similar story. The greatest differences in percentage points between female and male entrepreneurs are seen for business support to adopt AI legally / ethically / responsibly (40% for female / 29% for male), and greater confidence that AI adheres to data protection or copyright rules (53% / 41%). This is even more interesting when noting that the other solutions with the greatest gap in citation also link to legal and ethical adoption, namely, clear labelling or watermarking of AI-generated content (46% / 37%) and knowing where liability sits in supply chains if something goes wrong (38% / 28%). 40 per cent of female entrepreneurs of female entrepreneurs say that support to adopt AI legally, ethically and responsibly would help them adopt AI confidently, relative to 29 per cent of male.

“We’ve all seen the data on how men and women approach job descriptions differently. Men see that they meet half the requirements for a job and think, ‘I can do most of that’, but women think they’re underqualified unless they are confident they can do almost all of it. I think we’re seeing a similar difference in approach with AI.”

Deb Turner, FSB member, Property, South East England

Know-how in implementation is key for technology adoption

Data on barriers and incentives to the adoption of digital technologies more broadly shows that female entrepreneurs are more likely than their male counterparts to be being held back by a lack of know-how in implementation. For example, lack of know-how in implementation (34% / 29%) and uncertainty around where to start (26% / 18%) are more often cited by female than male entrepreneurs. Practical concerns, such as being able to access relevant business data (8% / 9%) and difficulties

finding a reliable software integrator (5% / 6%) are similar regardless of gender. In line with the finding that female entrepreneurs are more likely to cite barriers relating to a lack of know-how, female entrepreneurs are substantially more likely than their male peers to say that better information and guidance on how to implement (44% / 33%) and more awareness of potential benefits (44% / 32%) would incentivise them to adopt technology.

Support for legal, ethical and responsible AI adoption is key to closing the AI impact gap

These concerns do not appear to be functioning as a strong barrier to the adoption of AI, given that female business owners are slightly more likely to use AI (59%) than their male counterparts (56%). Instead, they are very likely limiting the ways in which female entrepreneurs are choosing to use AI within their businesses, which is limiting the benefits they are seeing as a result.

As shown above, female entrepreneurs are more likely to use AI for many lower-risk applications such as drafting emails (30% / 22%), but less likely to use it for more intensive tasks such as developing products and services (9% / 13%).

However, as noted above, concerns about ethical / legal / responsible implementation, and potential legal consequences, were felt particularly by female

entrepreneurs. And as seen in Figure 21, female business owners see lower productivity and revenue gains from AI (8% productivity gains and only 2% revenue gains, relative to 10% and 4% respectively for their male counterparts). This suggests that female entrepreneurs are adopting AI in a more controlled, lower-risk way in order to minimise legal risk, and the potential for implementing AI in a way that is not ethical or responsible. In practice, this may be in terms of the data and systems they allow AI access to, the extent to which workflows are automated, or the use of AI in sensitive contexts.

Support for legal, ethical and responsible adoption could impact how well-equipped female entrepreneurs feel regarding AI, as well as boosting overall rates of AI use among small businesses.

Chapter 6 – Moving between providers: Technology subscriptions

Subscriptions are a core part of how small businesses adopt and use technology, with 47 per cent saying that they subscribed to external software when adopting technology, and only 14 per cent saying that they do not have a technology subscription. However, small firms who use technology subscriptions often invest significant time and money into moving between systems, and face technical challenges when doing so.

Unpredictable and sometimes substantial cost rises are leaving some firms locked-in to software that they cannot afford. Addressing cost rises is vital in the short-term, but in the longer-term, software provided by large tech firms should be designed to be interoperable so small firms can easily and transparently switch to the technology that suits them best. This will be key to making sure that the

productivity benefits of business software accrue to small businesses and the economies they serve, rather than large tech firms.

As demonstrated in Figure 23, uncertainty and unpredictability of cost increases, alongside challenges moving data between online platforms, are common themes across subscriptions to different types of technology. Notably, challenges moving data between, and switching between, providers can mean that small businesses are ‘locked in’ to existing providers. They are then vulnerable to unexpected costs or price hikes. Ease of movement between platforms is key to allowing small firms to move across to the platforms and tools that suit them –and their budget – best at any given point in their technology journey.

Figure 23: Challenges faced by small businesses with technology subscriptions

Source: FSB AI & tech adoption survey, November 2025

Unpredictable cost increases

Uncertainty about costs

Unexpected adoption costs

Difﬁculties cancelling after a ‘free trial’

Difﬁculties switching between providers

Difﬁculties moving data between providers

Digital accountancy

65 per cent of survey respondents say they are using digital accountancy software. Users of digital accountancy are more likely than their peers to say that subscription costs have increased unpredictably (39% relative to 25% of those that do not use this technology), but not much more likely to cite unexpected or ‘hidden’ fees or costs in the adoption process (23% / 20%), suggesting that cost issues arise after implementation. They also cite difficulties switching between providers (22% / 13%) and moving data between providers (22% / 10%) more than their peers.

Qualitative research with small businesses also found that challenges around cost and switching between providers are acting as a strong deterrent to small businesses considering adopting the technology.

“I have two businesses. One’s a Community Interest Company, a repair café, and for that one we have a very cheap subscription to software that just does e-invoicing. For my main business we have a whole digital accountancy subscription that our accountant suggested we use. But the prices have been going up and up – to £40, nearly £50 a month. We can’t afford it. I’m talking with my accountant about moving away from that software altogether, and I’d be very hesitant about using that comprehensive sort of software for the CIC.”

Satheesh Pillai, FSB member, Entropy Advisors Ltd, London

This is especially concerning given that a number of recent measures by government have required small businesses to adopt digital accountancy tools. Making Tax Digital (MTD) for VAT-registered businesses was introduced as early as 2019.62 Initially for those with a turnover over £85,000 from April 2019, this was extended to all VAT-registered businesses (from April 2022). In December 2022, the Conservative Government announced that MTD will be mandatory for income tax self-assessment for sole traders and landlords with qualifying income over £50,000 from April 2026, and for those with qualifying income over £30,000 from April 2027.63 The current Government announced in March 2025 that this threshold would be lowered further to £20,000 from April 2028.64 MTD-compliant digital accountancy software is required for a small businesses to administer all of these changes, and share the data with HMRC.

Data analytics

Users of data analytics tools were more likely than their peers who do not use these tools to cite unexpected costs at the adoption stage (27% / 18%), as well as unpredictable increases in the cost of subscriptions themselves (41% / 29%). Difficulties moving data between providers was also more likely to be cited (23% / 14%), which is unsurprising given that data analytics tools often rely heavily on availability of data within systems.

AI use

Small businesses using AI are more likely to have a technology subscription (95%) than those that do not use AI (74%). Those using AI are more likely to have experienced each difficulty with technology subscriptions (and to have given an additional challenge under ‘Other’), but not substantially so. The greatest difference in percentage points is seen for unexpected or ‘hidden’ fees or costs in the adoption process, cited by 25 per cent of AI users and 18 per cent of non-AI users.

Looking at subscription challenges by AI use case, those that use AI to take notes in meetings are more likely than average to face unexpected or ‘hidden’ fees or costs in the adoption process (33% relative to an average of 22%) and to have experienced difficulties cancelling after a ‘free trial’ (29% / 19%). Businesses that use AI to edit or generate videos are most likely to say that subscription costs have increased unpredictably (43% relative to an average of 34%).

“You need lots of different tools to operate in a modern business environment. And if you want to use just one because it’s easier, you find that you need to pay for every additional functionality.”

Ruth Partington, Owner & Founder, Empower Translate, Wales

Difficulties moving data between providers are more likely to have been experienced by those using AI to draft or edit emails (28%, relative to an average of 18%). Difficulties switching between suppliers was more likely to be cited by those using AI to analyse trends and make projections (29%, relative to an average of 19%).

“The modern business environment is so complex – you need so many tools to navigate it. We use five or six regularly. But of course, not only do you have to work out which tools will do what your business needs in the way you want, you then have to work out which ones work together and how to link them up. We’re a pretty technical firm, but that can still be really challenging.”

Richard Askew, FSB member, Software business, North East England

Cloud computing

Users of cloud computing platforms are more likely than their peers to cite cost-related challenges regarding subscriptions, including overall uncertainty (29% of cloud-users relative to 17% of those who do not use cloud), unpredictable increases in costs (41% / 28%) and unexpected or ‘hidden’ fees or costs in the adoption process (27% / 18%). Perhaps relatedly, they also cite difficulties cancelling after a ‘free trial’ (24% / 14%). Although there is a less noticeable link between cloud use and difficulties switching between providers (23% relative to 15% of non-cloud users), difficulties moving data between providers saw a marked difference of 13 percentage points (25% / 12%).

Government competition measures on cloud and business software

The Digital Markets, Competition and Consumers Act 2024 gave the UK’s Competition and Markets Authority the power to designate large firms as having Strategic Market Status (SMS) following an SMS investigation lasting up to nine months. This allows the CMA to take specific actions relating to a designated business’ behaviour (conduct requirements) and its impact on competition in the wider market (pro-competition interventions).

FSB’s August 2023 report The Tech Tonic recommended that the Competition and Markets Authority should review and enforce data interoperability between different software that require large data input from SMEs, including cloud infrastructure.65

In October 2023, the CMA launched a market investigation for cloud service provision in the UK. The summary of the final decision, published in July 2025, notes that only 1 per cent of cloud customers switch providers each year, and while there is

some use of multiple cloud providers, this is more common for larger than smaller businesses. 66 Key barriers identified to using multiple cloud services at once, and switching between cloud providers, include technical barriers and egress fees (fees charged to customers moving data out of a cloud provider’s infrastructure). Within technical barriers, a lack of transparency about technical measures required to successfully move data between cloud providers is highlighted, reflecting concerns raised in this report. The CMA recommended opening of SMS investigations into Microsoft and Amazon Web Services (AWS) with regard to cloud service infrastructure provision.

These investigations concluded in March 2026.67 The CMA decided not to designate Microsoft or AWS as having SMS, opting instead for voluntary commitments from the two businesses in order to achieve the fastest resolution. Their focus instead shifts to an SMS investigation launched into Microsoft’s position in the market for business software, considered timely as an opportunity to shape the burgeoning market for AI tools, which are increasingly being embedded within business software packages. The focus on business software is welcome, as qualitative research with FSB members shows that small business owners face challenges when trying to use software from different providers, and will often not consider options outside of their existing business productivity software packages. Potential for interoperability with Microsoft 365 and Office products is unlikely to be a major barrier given Microsoft’s Open Specifications available for interoperators. However, poor visibility and communication around interoperable options, or ‘plug-ins’, seems to be a key factor.

“I regularly use AI tools such as Copilot and ChatGPT in different parts of my business. While I’m comfortable adopting new technology, one of the challenges as a small business owner is understanding how best to integrate these tools into existing systems and workflows so that their full potential can be realised.”

Gbemi Shitta, Founder, SweetDoughThings, London

Many of the voluntary commitments set out by Microsoft and AWS regarding their cloud computing platforms are welcome, especially those around providing 180 day free-egress switching windows. However, the lack of regulatory intervention fails

RECOMMENDATIONS

to reflect the fact that almost half (48%) of small businesses use cloud storage. Access to cloud storage is increasingly becoming a basic business utility - much like electricity or internet access. In the longer-term, the Department for Digital, Culture, Media & Sport should consider bringing cloud provision into Ofcom’s remit so it would be regulated in the same way as other utility providers. The focus of this would be on affordability and eradicating excess egress fees.

Other jurisdictions have made positive strides towards tackling barriers to switching between cloud providers. For instance, Articles 25, 27 and 30 of the EU Data Act 2023 set out requirements for cloud providers to provide contractual transparency about switching mechanisms and remove egress fees entirely.

The Department for Digital, Culture, Media & Sport should:

• Broaden the remit of Ofcom to include regulation of cloud services in the same way that utility providers are currently regulated. Under these proposals, Ofcom would be charged with ensuring that cloud infrastructure remains affordable, and providers do not charge excess egress fees.

• Convene a taskforce with industry and small businesses to look at providing a one-clickswitch experience for businesses moving their data from one cloud infrastructure provider to another. This should work towards the customer experience provided in other domains, such as to banking customers through the Current Account Switching Service (CASS), and could involve the use or development of open standards to allow cloud providers of all sizes to build their services for interoperability. This should work for both individuals and customers. This would remove the need for AI migration agents provided by specific large tech firms, although open standards to facilitate industry development of AI migration agents to meet technical challenges could also be considered.

Chapter 7 – Making the tech: Support for small tech firms

Small businesses in the tech sector have the potential to punch far above their weight. Supporting them does not require weakening of copyright protections, but clarification and simplification of regulatory environments, small business-focused

grant support for projects requiring relatively low sums, and fiscal support for the smallest firms conducting high-risk research and development. Enhanced access to compute for small AI firms could also be valuable.

Access to data and AI infrastructure

Access to internal business data in the relevant format is a barrier to adopting and making the best use of technology for some small firms. Indeed, 9 per cent of small businesses say that access to relevant business data is a barrier to them adopting or updating their technology. The importance of data for businesses’ use of technology is not new – FSB research in 2023 showed that only 22 per cent of small firms have seen no commercial benefits from using data – but as AI increasingly becomes a source of potential growth for small firms, being able to access internal data in the format needed is of growing importance.68

Qualitative research with FSB members has found that for small tech firms, training large AI models from scratch is not feasible – and often not necessary. Small businesses suggest that where they do train their own models, this is usually done using high-quality data sets to fine-tune existing models, using as little computational resource as possible. Quality of data sets and challenges navigating complex regulatory requirements were the key barriers raised.

“My business operates across nine countries and has been digital for nearly 30 years. We’ve generated a real wealth of data over that time, and it’s always been a challenge getting that into a format that we can use while accounting for data privacy and legal considerations. Agentic AI has been the solution for us. We’ve recently created an ‘AI champion’ role within the business, that’s to say, one of our team members who dedicates time to working on our agentic AI strategy and data management.”

Ruth Partington, Owner & Founder, Empower Translate, Wales

“A lot of what we do is just helping small firms work out what they need and then helping them work out the best tech for them. But when we do build bespoke software and AI for our clients, we almost always use open source models because it’s cheaper and we don’t have the capability to build our own. We have built our own database of different models as some are better for certain tasks than others.”

Patrick Kelly-Weller, Adapt Digital Ltd, London

For a small number, the cost of accessing compute to train AI models was also raised as a challenge. It should be noted that in April 2026, the Government’s Sovereign AI Unit opened applications for UK businesses to access part of its £500 million of funding for AI compute resource through the AI Research Resource, a public-private initiative.(initially launched with £500 million of compute available, 69 since doubled.)70 Recipients can be granted up to one million GPU hours.71 However, given that the minimum available investment is £1 million, this compute resource will likely only be made available to a small proportion of UK AI firms. Additionally, as AI itself makes it easier for those with less technical skillsets to build AI and other software (vibe coding), it is important that small firms across the economy have opportunities to develop or support the development of sector-specific and cross-sectoral AI models.

Grant funding

Nearly a quarter (24%) of small computer science and consultancy businesses say that access to more government grants would help them to adopt or update their technology, which is lower than the 30 per cent average for small businesses. This reflects feedback from FSB members that where they are eligible for innovation grants, the chances of success are so low that it often does not justify the time and resources required to apply. Innovation grants for small tech firms have not been prioritised in recent decisions, in particular by Innovate UK, ‘the UK’s innovation agency’ under UK Research and Innovation.

FSB members have provided consistently positive feedback on the scope and level of support provided by Innovate UK’s Smart Grants, with the only critique being that the grants were so popular that chances of success were low. These were grants for projects that include at least one small- or medium-sized business, taking place over up to two years, with a demonstrable and considerable economic value to the UK.72 Although grants could range from £100,000 to £2 million, feedback from previous recipients suggested awards to the smallest firms were often at the lowest end.

“We applied to Innovate UK for a Smart Grant and were turned down, despite submitting what we thought was a highquality application. The programme itself was well-scoped, but Smart Grants are just so competitive. With other programmes, it feels like the money often goes to the firms that were going to do the work anywayto those that least need it. They try to find ‘unicorns’ by betting only on those that are already quite far along.”

Satheesh Pillai, FSB Policy Champion, Tech, Entropy Advisors Ltd, London

Despite the programme’s clear value for innovative small firms, Innovate UK announced the pausing of their Smart Grants offer in January 2025, before eventually discontinuing the programme completely. This was disappointing as Innovate UK’s Smart Grants have been repeatedly oversubscribed, with less than 6 per cent of eligible applications in Streams 1 and 2 successful.73 The thresholds for success in both rounds were high at over 84

per cent, suggesting that a substantial number of eligible, high-quality projects went unfunded. This is a programme with an unusually high uptake from SMEs and high-quality applications, so would be a cost-effective focus for existing Innovate UK funding. A statement from Minister Narayan in December

Fiscal support

Fiscal support for innovation is consistently shown to be impactful, especially for the smallest firms for whom cost is a particular constraint. 34 per cent of small computer science and consultancy businesses say that increased tax reliefs or credits would help them to adopt or update their technology.

Previous FSB research clearly shows the impact of former and existing research and development (R&D) tax credits for small businesses. Of the small businesses which successfully applied for R&D tax relief from 2020 to 2023, it led to the following: improved the cashflow for their business (64%), increased their investment in R&D (55%), increased their investment in future projects (41%), and led to them undertaking projects that would not have happened otherwise (35%).76

In May 2025, HMRC consulted on introducing advance clearances for R&D tax reliefs, with the possibility of including a minimum expenditure threshold for claims, premised on the idea that the leanest innovation cannot be of relevant economic value. Alongside other respondents, FSB highlighted the disproportionate impact that such a threshold would have on the smallest firms. Much R&D work is collaborative, with both Innovate UK and Horizon Europe funding being allocated

2025 suggested that Innovate UK’s- focus has shifted to supporting ‘scaling innovative businesses in Industrial Strategy growth sectors’74 through their ‘Growth Catalyst’ scheme with a £130 million budget.75

specifically for partnership work between SMEs and larger collaborators (such as universities and large businesses). While the expenditure of a small partner on R&D may seem low, they form an essential part of the innovation ecosystem - introducing a minimum expenditure threshold would therefore undermine the whole ecosystem and risk pushing small firms out of valuable partnerships.

Introducing a minimum expenditure threshold would also undermine our international competitiveness. Making the R&D tax reliefs regime less attractive for small firms is likely to push them to outsource their R&D activity to overseas organisations. Pushing this innovative activity abroad can only have a chilling effect on our innovation ecosystem, and our goal of becoming a world-leading science and technology superpower.

This change would further compound the impacts of the R&D expenditure credit (RDEC) and SME R&D schemes having been merged into a new RDEC and enhanced R&D intensive support from the 2024/25 tax year. These changes have decreased the level of tax relief SMEs receive for R&D, which used to be subject to enhanced rates under the SME scheme, and instead have increased the rate of relief for large companies.

RECOMMENDATIONS

The UK Government should:

• Establish a national body with responsibility for stewardship of the UK’s open source industry. Recognising that most small firms do not have the resource to train ‘large’ AI models from scratch, this body would provide support and quality control for the open source industry, building on this area of existing UK strength and mitigating risks arising across AI supply chains due to adaptation of existing models. The body could also support government to integrate openness and interoperability requirements into technology procurement processes. This would reduce barriers for small tech companies to develop tailored products for government bodies that work with those bodies’ existing tech stacks, support competition in government procurement, and ultimately help government to get value for money. For sensitive contexts such as defence, this information could be made available only on request and at the discretion of the relevant government body. This could be a public-private initiative of the type proposed by OpenUK 77

The Department for Business, Innovation, Science & Trade should:

• Introduce requirements that data centres built to train or host AI models within AI Growth Zones make available a proportion of their compute to small businesses across sectors at a discounted rate. The Government’s AI Growth Zones programme aims to support investment in AI infrastructure by providing energy discounts, accelerated planning permissions, and other benefits.78 However, small businesses highlight that limited access to compute is a barrier to building AI models. This measure would help make sure the benefits of AI Growth Zones are shared across the economy. Alternatively, this could be achieved at the Local Authority level through agreements under Section 106 of the Town and Country Planning Act 1990.79

Innovate UK should:

• Resume Smart Grants with increased funding. Innovate UK announced the pausing of its Smart Grants offer from January 2025. This was disappointing as Innovate UK’s Smart Grants have been repeatedly oversubscribed, with less than 6% of eligible applications in Streams 1 and 2 successful. The thresholds for success in both rounds were high at over 84%, suggesting that a substantial number of eligible, high-quality projects went unfunded. This is a programme with an unusually high uptake from SMEs and high-quality applications, so would be a cost-effective focus for existing Innovate UK funding.

HM Treasury should:

• Commit to not introducing a Minimum Expenditure Threshold (MET) which would exclude the smallest innovators from accessing R&D tax credits. For 35 per cent of small businesses that have used R&D tax credits, it allowed them to undertake activities that they would otherwise not have done. HMRC chose not to rule out introducing a MET in its response to its 2025 consultation on R&D tax relief, leaving open the possibility of excluding claims from the smallest firms on the grounds that they are insufficiently expensive.80 Ruling this out would help give the smallest firms the certainty to invest in R&D activities. Treasury should also monitor the impact of the changes it has made to R&D tax relief that were announced in 2022 and 2023 fiscal events and publicly publish a review to assess the impact of the changes on levels of R&D conducted. If there has been a reduction in R&D activity due to the changes in tax relief, then the Treasury should increase the rate of relief for small businesses.

Methodology

This report is based on the views of FSB members as well as the wider small business population across the UK. FSB undertook a mixed research approach consisting of a quantitative online survey, focus groups and interviews. The survey was nationwide in its reach and participants were invited to complete the survey via email and social media channels. The survey was administered by the research agency Verve and was in the field from 11 to 24 November 2025. The survey questionnaire was completed by a total of 904 respondents. The focus groups took place via Microsoft Teams and purposefully drew from a variety of regions, nations, sectors, and population demographics. Focus groups and interviews took place on Microsoft Teams in January and February 2026.

References to data in this report are based on this survey, unless otherwise stated. Confidence intervals for the data are not included, but data has only been included where an adequate sample size has been achieved. The survey findings are weighted by region using the 2025 Business Population Estimates (BPE)

published by the Department for Business and Trade and the Office for National Statistics, to reflect the demographic balance of small businesses throughout the UK.81 All percentages derived from the survey are rounded to the nearest whole number, which is why some percentages presented in the figures may not sum to 100 per cent.

Sector breakdowns for the creative industries and high streets pull from other sectors and should therefore be considered alongside other sectoral analysis. The sector ‘Other’ refers to sectors captured by SIC code Section S, ‘Other service activities’, rather than all businesses that fall outside the other main sectors used for this analysis.

Endnotes

1 Please note that the September 2023 survey on AI asked about specific technologies (such as machine learning) rather than use case, whereas the November 2025 survey used for most of this report asked about use case (see Figure 2, below).

2 FSB, Signed, Sealed, Delivered, December 2025, https://www.fsb.org.uk/resources/ policy-reports/signed-sealed-deliveredMCGXDJ3J475NEPFOLCT6WGFAHFVU

3 As elsewhere in this report, the creative industries do not fit neatly within any of the other above sectors and have some overlap, so sit alongside other sectoral analysis. See the methodology for more.

4 Northern Ireland is not reflected due to insufficient sample size.

5 Small Business Index, Quarter 4 2025, February 2026, https://www.fsb.org.uk/ resources/reports/small-business-index/ small-business-index-quarter-4-2025MCKWUR6GFLWVALLECTVNKPS7FKMQ

6 FSB, New research shows scale to which Labour’s employment plan will harm jobs, lock people out of work and cause spiralling benefits bill, January 2025, https://www.fsb. org.uk/media-centre/press-release/newresearch-shows-scale-to-which-labour-semployment-plan-will-harm-jobs-lock-pMCBJELDTY47NE53M57XBTX3AIUOY

7 Gaps in this and following tables are due to non-applicability or insufficient sample size.

8 Agrawal, McHale& Oettl, Finding Needles in Haystacks: Artificial Intelligence and Recombinant Growth, May 2019, https:// www.nber.org/books-and-chapters/ economics-artificial-intelligence-agenda/ finding-needles-haystacks-artificialintelligence-and-recombinant-growth

9 Siedschlag & Duran, Artificial Intelligence and Firm -Level Productivity: Early Evidence from a Small Open Economy, December 2025, https://www.productivity.ac.uk/wp-content/ uploads/2025/12/WP63.pdf

10 Brynjolfsson, Rock & Syverson, THE PRODUCTIVITY J-CURVE: HOW INTANGIBLES COMPLEMENT GENERAL PURPOSE TECHNOLOGIES, 2019, https://ide.mit.edu/sites/default/files/ publications/2019-04JCurvebrief.final2_.pdf

11 Siedschlag & Duran, Artificial Intelligence and Firm-Level Productivity: Early Evidence from a Small Open Economy, December 2025, https://www.productivity.ac.uk/wp-content/ uploads/2025/12/WP63.pdf

12 Systma, The Dynamics Behind Artificial Intelligence’s Impact on Productivity Growth, December 2025, https://www.rand.org/pubs/ perspectives/PEA4392-1.html

13 Department for Science, Innovation & Technology and Department for Energy Security & Net Zero, AI Energy Council minutes: Monday 1 December 2025 (HTML), December 2025, https://www.gov.uk/ government/publications/ai-energy-councilmeetings-minutes/ai-energy-councilminutes-monday-1-december-2025-html

14 Department for Science, Innovation & Technology and Department for Culture, Media & Sport, Copyright and AI Impact Assessment, March 2026, https://assets.publishing.service.gov.uk/ media/69ba68f7c06ba9576435abb0/ CP2602959_-_AI_and_Copyright_Impact_ Assessment_Web.pdf

15 FSB, Creating Change, November 2025, https://www.fsb.org.uk/resources/ policy-reports/creating-changeMCRU3TMSQRD5G5RLYF2NQBH34CSY

16 FSB, Redefining Intelligence, March 2024, https://www.fsb.org.uk/resource-report/ redefining-intelligence.html

17 Coalition for Content Provenance and Authenticity, https://c2pa.org/

18 Shumailov, Shumaylov, Zhao, et al., AI models collapse when trained on recursively generated data, July 2024, https://doi. org/10.1038/s41586-024-07566-y

19 Ada Lovelace Institute, Risky business, December 2025, https://www. adalovelaceinstitute.org/report/riskybusiness/

20 Bengio et al., International AI Safety Report, January 2025, https://arxiv.org/ pdf/2501.17805

21 Liu et al., Prompt injection attack against LLM-integrated Applications, June 2023, https://arxiv.org/abs/2306.05499

22 Department for Science, Innovation & Technology, Policy paper: Incident reporting, March 2026, https://www.gov. uk/government/publications/cyber-securityand-resilience-network-and-informationsystems-bill-factsheets/incident-reporting

23 Department for Science, Innovation and Technology and Feryal Clark MP, Cyber Essentials scheme: overview, March 2026, https://www.gov.uk/government/ publications/cyber-essentials-schemeoverview

24 National Cyber Security Centre, Cyber Essentials, https://www.ncsc.gov.uk/ cyberessentials/overview

25 Department for Science, Innovation and Technology, Cyber Essentials management information, March 2026, https://www.gov. uk/government/statistical-data-sets/cyberessentials-management-information

26 Department for Science, Innovation & Technology, Cyber Essentials scheme process evaluation, June 2023, https://www. gov.uk/government/publications/cyberessentials-scheme-process-evaluation/ cyber-essentials-scheme-process-evaluation

27 Crown Commercial Service, Procurement Policy Note – Cyber Essentials Scheme, May 2016, https://assets.publishing.service.gov. uk/media/5a816448e5274a2e87dbd61a/ ppn_update_cyber_essentials_0914.pdf

28 Cyber Essentials Supply Chain Playbook, December 2025, https://www.ncsc.gov.uk/ information/cyber-essentials-supply-chainplaybook

29 International Organisation for Standardization, ISO/IEC 42001:2023, December 2023, https://www.iso.org/ standard/42001

30 Financial Conduct Authority, AI and the FCA: our approach, September 2025, https:// www.fca.org.uk/firms/innovation/ai-approach

31 Financial Conduct Authority, AI Lab, March 2026, https://www.fca.org.uk/firms/ innovation/ai-lab

32 https://committees.parliament.uk/ committee/158/treasury-committee/ news/211401/current-approach-to-ai-infinancial-services-risks-serious-harm-toconsumers-and-wider-system/

33 House of Lords Communications and Digital Committee, Digital regulation: joined-up and accountable, December 2021, https:// committees.parliament.uk/publications/8186/ documents/83794/default/

34 Department for Science, Innovation & Technology, Cyber Essentials scheme process evaluation, June 2023, https://www. gov.uk/government/publications/cyberessentials-scheme-process-evaluation/ cyber-essentials-scheme-process-evaluation

35 University of Helsinki and MinnaLearn, Elements of AI, https://www.elementsofai. com/

36 Government Digital Service, Guidelines for AI procurement, January 2025, https://www. gov.uk/data-ethics-guidance/guidelines-forai-procurement

37 Coalition for Content Provenance and Authenticity, https://c2pa.org/

38 Department for Science, Innovation & Technology, Guidance: Code of Practice for the Cyber Security of AI, January 2025, https://www.gov.uk/government/ publications/ai-cyber-security-code-ofpractice/code-of-practice-for-the-cybersecurity-of-ai

39 Intellectual Property Office, The Collective Management of Copyright (EU Directive) Regulations 2016: How the IPO will carry out investigation and enforcement activities, January 2021, https://www.gov.uk/government/ publications/how-the-ipo-will-carry-outinvestigation-and-enforcement-activities/ the-collective-management-of-copyrighteu-directive-regulations-2016-how-theipo-will-carry-out-investigation-andenforcement-activities

40 Foreign Affairs Committee, Disinformation diplomacy: How malign actors are seeking to undermine democracy, March 2026, https://committees.parliament.uk/ publications/52401/documents/290829/ default/

41 FSB, The Tech Tonic, August 2023, https:// www.fsb.org.uk/resource-report/the-techtonic.html

42 Innovate UK, https://www.ukri.org/councils/ innovate-uk/

43 HM Treasury, Budget 2025 (HTML), November 2025, https://www.gov.uk/ government/publications/budget-2025document/budget-2025-html

44 Innovate UK BridgeAI, Bridging the AI divide, March 2026, https://iuk-business-connect. org.uk/wp-content/uploads/2026/03/ BridgeAI_Report_050326.pdf

45 Department for Science, Innovation & Technology, AI Skills Boost: explainer, January 2026, https://www.gov.uk/ government/publications/ai-skills-boostexplainer/ai-skills-boost-explainer

46 Science, Innovation and Technology Committee, Oral evidence: Work of UK Research and Innovation (UKRI), HC 1673, February 2026, https://committees. parliament.uk/oralevidence/17145/pdf/

47 Department for Business & Trade, SME Digital Adoption Taskforce: final report, July 2025, https://www.gov.uk/government/ publications/sme-digital-adoption-taskforcefinal-report/sme-digital-adoption-taskforcefinal-report

48 Based on 2024 estimates of SME turnover in the UK totalling £2.8 trillion. Assuming linear relationship between technology adoption and revenue gains, based on the 55% of AI users seeing an additional 1.5% annual revenue gains, and half of the 45% of small businesses not currently using AI adopting it and seeing 3% revenue gains. Turnover figure from: Department for Business & Trade, Business population estimates for the UK and regions 2025: statistical release, October 2025, https://www.gov.uk/ government/statistics/business-populationestimates-2025/business-populationestimates-for-the-uk-and-regions-2025statistical-release

49 Artificial Intelligence Collaboration Centre, https://www.aicc.co/

50 Scottish Government, Scotland’s AI Strategy: 2026 – 2031, March 2026, https://www. gov.scot/binaries/content/documents/ govscot/publications/strategy-plan/2026/03/ scotlands-ai-strategy-2026-2031/ documents/ai-strategy-scotland/ai-strategyscotland/govscot%3Adocument/ai-strategyscotland.pdf

51 Office for National Statistics, Young people not in education, employment or training (NEET), UK: November 2025, November 2025, https://www.ons.gov.uk/employmentandlabourmarket/peoplenotinwork/ unemployment/bulletins/youngpeoplenotineducationemploymentortrainingneet/november2025

52 Department for Work & Pensions, The employment of disabled people 2025, March 2026, https://www.gov.uk/government/ statistics/the-employment-of-disabledpeople-2025/the-employment-of-disabledpeople-2025

53 FSB, Entrepreneurs, start ups and business growth, December 2024, https://www.fsb.org.uk/resources/ policy-reports/entrepreneursstart-ups-and-business-growthMCBX5USEDCLNGGVC4IHDEB42ZHSQ

54 Department for Work and Pensions, New Enterprise Allowance statistics: April 2011 to December 2021, June 2022, https:// www.gov.uk/government/statistics/ new-enterprise-allowance-april-2011-to december-2021

55 Department for Business & Trade, SME Digital Adoption Taskforce: final report, July 2025, https://www.gov.uk/government/ publications/sme-digital-adoption-taskforcefinal-report/sme-digital-adoption-taskforcefinal-report

56 Department for Science, Innovation & Technology, Digital Inclusion Innovation Fund, https://www.gov.uk/government/ publications/digital-inclusion-innovationfund/digital-inclusion-innovation-fund

57 Ofcom, General Conditions of Entitlement, April 2026, https://www.ofcom.org.uk/ phones-and-broadband/accessibility/ general-conditions-of-entitlement

58 BMG Research for the Department for Business & Trade, Made Smarter Adoption Research project, February 2023, https://assets.publishing.service.gov.uk/ media/65e06d14cf7eb1b0e5f57f3e/madesmarter-adoption-report.pdf

59 Please see footnote 51 on page 31 for methodology.

60 Business and Trade Committee, Small business strategy, February 2026, https://committees.parliament.uk/ publications/51536/documents/288743/ default/

61 FSB, The Tech Tonic, August 2023, https:// www.fsb.org.uk/resource-report/the-techtonic.html

62 HM Revenue & Customs, Making Tax Digital for VAT is coming – are you ready?, January 2022, https://www.gov.uk/government/ news/making-tax-digital-for-vat-is-comingare-you-ready

63 UK Parliament, HMR Revenue and Customs Update: Statement made on 19 December 2022, December 2022, https:// questions-statements.parliament.uk/writtenstatements/detail/2022-12-19/hcws465

64 HM Treasury, Spring Statement 2025, March 2025, https://assets.publishing.service.gov. uk/media/67e3ec2df356a2dc0e39b488/ E03274109_HMT_Spring_Statement_ Mar_25_Web_Accessible_.pdf

65 FSB, The Tech Tonic, August 2023, https:// www.fsb.org.uk/resource-report/the-techtonic.html

66 Competition and Markets Authority, Cloud Services Investigation: Summary of final decision, July 2025, https:// assets.publishing.service.gov.uk/ media/688b20e6ff8c05468cb7b120/ summary_of_final_decision.pdf

67 Competition and Markets Authority, Actions on cloud and business software through the UK digital markets competition regime, March 2026, https://assets.publishing.service.gov. uk/media/69cbb8d52d120d9d5ec0f311/ Actions_on_cloud_and_business_software_ through_the_UK_digital_markets_ competition_regime.pdf

68 FSB, The Tech Tonic, August 2023, https:// www.fsb.org.uk/resource-report/the-techtonic.html

69 Department for Science, Innovation & Technology, AI Opportunities Action Plan: One Year On, January 2026, https:// www.gov.uk/government/publications/aiopportunities-action-plan-one-year-on/aiopportunities-action-plan-one-year-on

70 Sovereign AI, We’re DOUBLING Compute Access for the UK’s Most Ambitious AI Startups, June 2026, https://www. sovereignai.gov.uk/post/were-doublingcompute-access-for-the-uks-mostambitious-ai-startups

71 Sovereign AI, https://www.sovereignai.gov. uk/

72 UK Research and Innovation , Smart Grants funding guidance, February 2026, https:// www.ukri.org/councils/innovate-uk/guidancefor-applicants/guidance-for-specific-funds/ smart-innovation-funding-guidance/

73 UK Research and Innovation, FOI Response Letter FOI2021 00116, March 2021, https://www.whatdotheyknow.com/ request/innovate_uk_smart_grants_august/ response/1748250/attach/html/3/FOI%20 Response%20Letter%20FOI2021%20 00116.pdf.html

74 UK Parliament, Innovate UK: Grants: Question for Department for Science, Innovation and Technology, December 2025, https://questions-statements.parliament.uk/ written-questions/detail/2025-12-02/96113/

75 Innovate UK Business Connect, Innovate UK Growth Catalyst – Investor Partnerships Round 2 , December 2025, https://iuk-business-connect.org.uk/ opportunities/innovate-uk-growth-catalystdecember-2025/

76 FSB, The Tech Tonic, August 2023, https:// www.fsb.org.uk/resource-report/the-techtonic.html

77 OpenUK, Making the UK the Home of Open Source, March 2026, https://openuk.uk/wpcontent/uploads/2026/03/Making-the-UKthe-Home-of-Open-Source-1.pdf

78 Department for Science, Innovation & Technology, AI Opportunities Action Plan: One Year On, January 2026, https:// www.gov.uk/government/publications/aiopportunities-action-plan-one-year-on/aiopportunities-action-plan-one-year-on

79 Town and Country Planning Act 1990, https://www.legislation.gov.uk/ ukpga/1990/8/section/106

80 HM Revenue & Customs, Research and development tax relief advance clearances – Summary of responses, November 2025, https://www.gov.uk/government/ consultations/research-and-developmenttax-relief-advance-clearances/outcome/ research-and-development-tax-reliefadvance-clearances-summary-of-responses

81 Department for Business and Trade, Business population estimates 2025, October 2025, https://www.gov.uk/ government/statistics/business-populationestimates-2025

fsb.org.uk

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