While financial services firms race ahead with 75% AI adoption, manufacturing languishes at 5%—and 43% of SMEs have no plans to catch up. A new government report reveals the stark reality of Britain’s digital divide.
The United Kingdom is sleepwalking into a two-tier economy. While City firms harness artificial intelligence to supercharge productivity and profits, the businesses that form the backbone of Britain’s economy—manufacturers, retailers, and high street SMEs—are being left behind in what could become the defining economic divide of our generation.
A landmark government report published this summer lays bare the scale of the challenge. The SME Digital Adoption Taskforce found that 43% of UK small and medium-sized enterprises have no plans to adopt AI, leaving a potential £94 billion in annual GDP growth on the table. But dig deeper into the data, and a more troubling picture emerges: this isn’t just about slow adoption—it’s about a fundamental split in the UK economy between AI “haves” and “have-nots.”
The 70-Point Gap: Financial Services vs Manufacturing
The numbers are stark. In the financial services sector, 75% of firms are now actively using AI—a dramatic increase from 58% just three years ago in 2022. These institutions are deploying machine learning for fraud detection, algorithmic trading, customer service automation, and risk assessment. The result? Unprecedented efficiency gains and competitive advantages that compound with each passing quarter.
Meanwhile, in the manufacturing sector—the industry that built modern Britain—AI adoption sits at a dismal 5%. Even within manufacturing, adoption is patchy: textiles lead at 11%, but most subsectors remain firmly in single digits. This 70-percentage-point gap between financial services and manufacturing represents more than just a technology divide—it’s a chasm that threatens to reshape the entire UK economic landscape.
The services sector overall fares only marginally better, with 9% adoption across the board. The information and communication industry leads at 27%, but this masks the reality for most service businesses. Customer-facing firms—the restaurants, shops, and local service providers that employ millions—are particularly vulnerable, with 50% having no plans to adopt AI at all.
The £94 Billion Question: Why Are AI for SMEs is Stalling?
The government’s SME Digital Adoption Taskforce calculated that a mere 1% productivity uplift across the UK’s 5.5 million SMEs would add £94 billion annually to GDP. Given that AI for SMEs has been proven to boost productivity by anywhere from 27% to 133% according to University of St Andrews research, this figure is not just achievable—it’s conservative.
So why are nearly half of UK SMEs refusing to engage? The research reveals a complex web of barriers:
Knowledge Gap: Only one-third of small business leaders report having even a basic understanding of AI. This isn’t about technical expertise—it’s about fundamental awareness of what AI can do and how it might apply to their business.
Use Case Paralysis: The most common barrier, cited by 39% of firms, is difficulty identifying where AI could help their business. Without clear examples relevant to their sector, business leaders struggle to see beyond the hype.
Cost Concerns: 30% of businesses cite high costs as their primary concern, though this often reflects uncertainty rather than reality. Many assume AI requires massive investment in infrastructure and expertise, unaware that accessible, affordable tools now exist.
ROI Uncertainty: A quarter of businesses (25%) are held back by uncertainty around return on investment—a chicken-and-egg problem where lack of understanding prevents the very experimentation that would demonstrate value.
Skills Shortage: 35% lack the necessary in-house expertise, and with 43% of employers struggling to fill technical roles, this barrier is only getting worse.
The Regulatory Advantage: Britain’s Measured Approach
Amid this adoption crisis, the UK has made one decision that may prove crucial for SMEs: it has resisted the urge to regulate prematurely. While the European Union rushed to implement its comprehensive AI Act—imposing mandatory compliance obligations and categorising AI systems into risk tiers—the UK has taken what it calls a “pro-innovation” approach.
When criticised in Parliament for “dragging its feet,” then-Science Secretary Michelle Donelan’s response was blunt: the claim was “absolute tosh.” The UK is deliberately avoiding laws that could be “outdated upon arrival,” preferring to understand the risks thoroughly before legislating.
Instead of new AI-specific laws, the government published its AI Regulation White Paper in March 2023, establishing five cross-sectoral principles that existing regulators should apply: safety and robustness; transparency and explainability; fairness; accountability and governance; and contestability and redress. Critically, these principles are non-statutory—they’re guidance, not law. The government has backed this with over £100 million in investment, including funds for the world’s first AI Safety Institute.
For SMEs already struggling with a 39% “use case identification” barrier and 30% cost concerns, this restraint matters. The UK’s model relies on proportionality—regulators are explicitly instructed to avoid placing “undue burdens” on businesses. A manufacturer using AI to optimise inventory faces fundamentally different risks than a bank deploying AI for credit decisions, and the UK’s context-based approach recognises this reality.
The Financial Conduct Authority makes this explicit: systemic risks come primarily from critical third-party providers and large institutions, not from individual SMEs experimenting with productivity tools. An SME using AI to draft marketing emails doesn’t pose the same systemic risk as a major bank deploying algorithmic trading systems.
This is not an argument for permanent regulatory absence. The government has indicated it will legislate “in the next year,” and when that legislation arrives, the UK will have had time to observe real-world deployment and design evidence-based rules. For SMEs, this sequencing matters: premature regulation could have locked in compliance costs at precisely the moment when businesses need maximum flexibility to experiment and learn.
The challenge now is ensuring that when mature regulation does arrive, it maintains this proportionality principle—recognising that a Yorkshire heating company using AI for sales follow-ups is not the same as a tech giant training foundation models. Get that balance right, and the UK could bridge its two-tier economy. Get it wrong, and regulation could cement the divide permanently.
The Success Stories They’re Ignoring
The tragedy of this inaction is that the blueprint for success already exists. UK SMEs that have embraced AI are achieving transformative results:
Trust Electric Heating, a Yorkshire-based SME, achieved a 500% productivity increase in sales follow-ups after implementing AI tools. The company tripled its workforce, operations, and turnover in just two years, while simultaneously halving its cost per lead. “AI has become like a personal assistant for everyone—one that works around the clock,” says co-owner Fiona Conor.
OnBuy.com, the e-commerce marketplace, transformed from a £1 million monthly loss to nearly £20 million in gross profit over 12 months by becoming AI-driven. The company estimates AI saved it 25 years of development time and tens of millions of pounds.
Deep.Meta, a steelmaking technology firm, developed an AI platform that reduced energy consumption by 24 kWh per tonne of steel, cut CO2 emissions by 5%, and improved productivity by 20%. One operator with 30 years of experience reported the tool made his job “five times faster.”
These aren’t tech unicorns or Silicon Valley transplants—they’re traditional UK businesses that recognised AI as a tool for survival and growth, not a luxury for the elite.
The Compounding Cost of Inaction
The two-tier economy isn’t just about missed opportunities—it’s about active economic damage. The UK now ranks 25th worldwide for future digital readiness, down from more competitive positions in previous years. Only one in five UK firms have high digital adoption, compared to half of all firms in Denmark and two in five in the Netherlands.
This decline is compounded by a crippling digital skills gap. The lack of essential digital skills in the UK workforce is costing the economy over £23 billion per year, with projections suggesting this will grow to £27.6 billion by 2030, alongside the loss of 380,000 jobs. More than half of working-age adults (52%) cannot complete all 20 tasks considered essential for work in a digital world.
The result is a vicious cycle: firms don’t adopt AI because they lack skills and understanding, which means they fall further behind competitors, which makes investment in catching up seem even more daunting.
A Call to Action: Bridging the Divide
The two-tier economy is not inevitable. Phil Smith CBE, Chair of the SME Digital Adoption Taskforce, has set an ambitious goal: “to make UK SMEs the most digitally capable and artificial intelligence confident in the G7 by 2035.”
Achieving this requires action on multiple fronts:
For Government: The Taskforce’s 10 recommendations include appointing a minister accountable for SME digital adoption, developing a scalable online “CTO as a service” to provide AI-powered guidance, and launching targeted awareness programmes. The £7.4 million AI Upskilling Fund was a start, but sustained, scaled support is essential.
For Business Leaders: The evidence is clear—AI for SMEs is no longer optional for competitiveness. But it doesn’t require massive investment or technical transformation. Accessible tools exist for invoicing (ANNA Money), customer service (Intercom’s Fin AI), marketing (HubSpot, Mailchimp), and workflow automation (Zapier). The key is starting small, identifying one clear use case, and building from there.
For Sectors: Industry bodies must step up to provide sector-specific guidance and case studies. A manufacturer needs different AI applications than a retailer, and generic advice won’t cut through the noise.
The Choice Ahead
Britain stands at a crossroads. One path leads to an entrenched two-tier economy where a small elite of AI-enabled firms pull away from the pack, concentrating wealth and opportunity while traditional businesses struggle and fail. The other path leads to broad-based adoption, where the £94 billion opportunity is shared across sectors and regions, strengthening the entire economic foundation.
The technology exists. The business case is proven. The only question is whether UK SMEs—and the policymakers who support them—will seize the opportunity before the gap becomes unbridgeable.
The great divide is real. But it’s not yet permanent.
About the Author
Nick Harding is Co-Founder of Fifty One Degrees, a London-based AI and data consultancy that specialises in empowering UK businesses in financial services, home improvements, insurance, retail, and energy sectors to harness AI for growth and innovation. Fifty One Degrees is a keen supporter of AI for SMEs.
A more detailed analysis, including additional data and expert commentary, is available in the News & Research section of the Fifty One Degrees website.
