UK's AI Future: Prioritize Deployment & Infrastructure, Says Tony Blair Institute

The United Kingdom should prioritize the widespread adoption and deployment of artificial intelligence (AI) rather than attempting to compete with global superpowers in the development of cutting-edge AI models. This is the central recommendation from the Tony Blair Institute for Global Change (TBI), which warns that even a focus on AI deployment will necessitate a significant increase in the UK's domestic compute capacity and a serious commitment to infrastructure development.

According to the TBI's recent report, the UK lacks the substantial resources—including financial capital, available land, and energy—required to rival the colossal investments being made by the United States, China, and the Gulf States in vast, energy-intensive datacenters for AI training. Instead, the institute argues, Britain's economic gains will be found in demonstrating effective AI application across critical sectors like health, education, government, defense, and science, thereby boosting productivity, enhancing public services, and stimulating innovation.

However, pursuing this deployment-focused strategy is still contingent on considerable investment in AI infrastructure. While the UK government has acknowledged this need in its "AI Opportunities Action Plan" and "Compute Roadmap," the TBI contends that these measures are insufficient. The report describes the current situation as "dire," noting that despite AI being central to the UK's growth and security ambitions, the necessary infrastructure is lagging. At its current pace, the UK is unlikely to achieve its 2030 target of 6 gigawatts (GW) of AI-ready capacity. Key impediments include planning and permitting delays, constraints within the national grid, and escalating industrial energy costs.

This assessment is reinforced by a separate report from fDi Intelligence, a division of the Financial Times, which projects a potential 5 GW shortfall in the UK's datacenter compute capacity. Based on an analysis commissioned by the Department for Science, Innovation & Technology (DSIT), this forecast anticipates demand between 5.1 GW and 8.5 GW by 2030, while supply is projected to reach only 3.3 GW from the current 1.8 GW. Most of the existing capacity is concentrated around London and is not optimized for AI workloads.

To address these challenges, the Tony Blair Institute advocates an "accelerated diversification" strategy for building resilient infrastructure. This involves attracting new investment by reducing risk, regionally distributing compute capabilities to enhance resilience, and fostering a robust domestic ecosystem. Specific recommendations include:

• Energy Integration: Ensuring the National Energy System Operator (NESO) fully integrates datacenter demand into national energy plans and supports this through dynamic updates. The report also suggests forming a dedicated team of AI and datacenter experts within NESO to aid demand planning and accelerate AI integration into the energy system.
• Planning Reform: Amending the planning process to ensure decisions are issued within an eight-month period and utilizing ministerial "call-in" powers for high-investment datacenter and grid projects. The government has already designated large server farms as Critical National Infrastructure (CNI) and Nationally Significant Infrastructure Projects (NSIPs), allowing developers to bypass some local planning hurdles.
• Energy Generation: Adopting a strategy to develop new gigawatt nuclear power stations and reforming nuclear regulation to expedite construction and reduce costs.
• Land Use: Modifying regulations to permit the co-location of AI datacenters with energy generation sources and identifying government-owned land for private developers to build datacenters.

The TBI acknowledges that these recommendations represent a substantial undertaking for any UK government, often characterized by slow decision-making and chronic budget constraints.

Despite these calls to action, there are growing concerns within the industry about the potential for an AI hype bubble. A McKinsey & Company report highlighted widespread uncertainty regarding future AI demand. Other research indicates that generative AI has yet to show a significant impact on earnings or recorded work hours, despite billions invested in model development and training. Gartner predicts that 40 percent of agentic AI projects could be abandoned by the end of 2027 due to rising costs, unclear business value, or insufficient risk controls. Furthermore, Baidu CEO Robin Li described the AI sector as being in an "inevitable bubble," akin to the dot-com era, and a Lenovo report found that only 4 out of 33 surveyed AI proof-of-concept projects progressed to production, a high failure rate.

Nevertheless, the UK government and the Tony Blair Institute remain resolute in their conviction that strategic investment in AI infrastructure is paramount. The TBI concludes that failure to build will lead to the UK falling behind, while success in building the right infrastructure and gaining expertise in AI application presents a genuine opportunity for global leadership.