Artificial intelligence has quickly shifted from hype to hard numbers in the UK economy. By 2023, UK AI companies were generating £14.2 billion in revenues, employing more than 64,000 people, and contributing £5.8 billion in Gross Value Added (GVA). In 2024, the sector’s market value surged to an estimated £72 billion, placing Britain firmly as the third-largest AI economy in the world, behind only the US and China.
Forecasts suggest that by 2025 the market could exceed £80 billion, with long-term projections pointing to a trillion-pound sector by 2035. The UK’s AI ecosystem has grown by more than 17% in company numbers in a single year, and employment in the sector has expanded by almost 30%.
On the surface, these are remarkable figures — validation of years of government funding, private investment, and academic research. But behind the rapid growth are two structural imbalances that, if left unaddressed, could weaken the UK’s long-term position: its geographic concentration and its SME squeeze.
The London Problem
Around three-quarters of all AI firms in the UK are registered in London, the South East, or East of England. This is no accident. The capital is home to world-leading universities such as UCL and Imperial, a critical mass of talent, and the financial and legal sectors that have both the money and the appetite to adopt AI early.
This clustering has been a strength: London has emerged as one of the world’s major AI hubs, home to DeepMind, Faculty, and a growing cohort of startups. The density of expertise has also attracted global players Amazon, Microsoft, Google to expand their AI footprints in the UK.
But it comes with risks. Other parts of the UK are missing out. The Midlands automotive corridor, the North East’s energy sector, and agritech in the South West are industries where AI could have a profound impact on productivity. Yet these sectors remain under-served, largely because the gravitational pull of London dominates investment and talent flows.
As one academic quoted in the government’s AI Sector Study warned: “The danger is that we are largely concentrated in London and the South East. We need more resilience and breadth of activity.”
The SME Squeeze
The second imbalance is structural rather than geographical. The UK’s AI sector is overwhelmingly driven by small firms. 96% of AI companies are SMEs, and nearly two-thirds are micro-businesses with fewer than 10 employees. These firms are the ones pushing boundaries — experimenting with niche applications, developing new products, and pivoting fast in response to opportunities.
Yet the financial spoils lie elsewhere. Just 4% of large firms capture around 80% of sector revenues (£11.4 billion). Diversified giants and global tech firms can afford the compute power, talent, and data pipelines that smaller players cannot.
The barriers for SMEs are significant:
- Access to equity — more than half of AI firms cite lack of funding as their primary obstacle.
- Infrastructure costs — training data, compute power, and storage remain expensive.
- Talent shortages — 26% of firms report being hampered by the scarcity of skilled AI professionals, a figure amplified by competition from global giants offering higher salaries.
This creates a polarised market. At one end, the large, diversified players dominate revenue and employment. At the other, fragile innovators drive creativity but struggle to scale. The “missing middle” — scale-ups that could bridge the gap — is thin on the ground.
A Market at Risk of Polarisation
These two dynamics — London’s dominance and the SME squeeze — combine to create a market at risk of polarisation. If the UK becomes overly dependent on London and on a small set of large firms, it risks hollowing out the broader ecosystem.
The danger isn’t just about fairness or regional balance. It’s about resilience. A healthy AI economy depends on diversity — of regions, of company sizes, of applications. Without it, the UK risks building a trillion-pound industry on a narrow and fragile base.
What Needs to Change
If the UK is serious about becoming a global AI leader, four priorities stand out.
- Spread investment beyond London. Direct funding, incentives, and infrastructure into regional hubs. The Midlands could become a world leader in automotive AI; the North East could harness AI for energy and utilities; the South West could scale agritech. These industries already have expertise and need only the AI fuel to ignite growth.
- Support SME scale-ups. Micro-businesses are doing the hard innovation, but too many fail to cross the “valley of death” between prototype and commercial success. Compute credits, targeted growth funds, and tailored export support could help them scale sustainably.
- Fix the bottlenecks. SMEs can’t compete if the cost of compute and access to data remain prohibitive. National infrastructure investments in compute capacity, data-sharing frameworks, and training pipelines could level the playing field.
- Nurture regional clusters. Universities, startups, and corporates working together have proven powerful in the South East — think Cambridge biotech or London fintech. Replicating that model in other regions could create a more balanced national AI economy.
A Trillion-Pound Question
The UK has the research base, the entrepreneurs, and the political ambition to lead in AI. But leadership won’t come from London alone, nor will it come from a handful of global giants capturing the rewards.
If AI is to deliver on its promise — driving productivity in manufacturing, healthcare, agriculture, and public services — the UK must ensure that growth is broad, balanced, and sustainable. That means spreading investment, backing SMEs, fixing the bottlenecks, and building regional clusters.
Otherwise, the UK risks building a trillion-pound AI sector on uneven foundations — and discovering too late that growth concentrated at the top is no substitute for resilience at the base.
