Kao Data Offers Roadmap for UK AI Infrastructure Strategy

Kao Data has published a report setting out measures to support the UK government's AI infrastructure plans, which have attracted £31bn (US$41.3bn) in commitments from US technology companies. 

The blueprint addresses the operational requirements needed to convert financial pledges from Microsoft, Google, NVIDIA, OpenAI and CoreWeave into functioning data centre capacity.

The report, titled "AI Taking, Not Making," examines the relationship between government policy and private sector infrastructure development. It identifies energy pricing, grid capacity and copyright legislation as areas that require attention to enable the deployment of AI infrastructure at scale.

Kao Data identifies energy and grid priorities

The company's analysis centres on three areas that will determine whether the UK can accommodate the computing infrastructure needed for AI development. 

Energy pricing structures, grid modernisation timelines and cross-sector investment coordination form the basis of the recommendations.

In January 2025, the UK Prime Minister Keir Starmer announced the AI Opportunities Action Plan and Tech entrepreneur Matt Clifford was tasked with developing the action plan which makes 50 recommendations across key areas, including improving data capabilities and access, alongside crucial commitments like a 20-fold increase in public compute capacity by 2030 and a specified role to support sovereign AI capabilities.

Spencer Lamb, Managing Director and Chief Commercial Officer of Kao Data says: "Matt Clifford's AI Opportunities Action Plan has galvanised the industry around a bold vision for Britain's digital future, and the recent investment pledges from global technology leaders signals tremendous confidence in our potential.

"What's needed now is focused collaboration between industry and government to transform these commitments into world-class infrastructure."

The report proposes that data centres should be included in Energy Intensive Industry frameworks, which currently apply to manufacturing sectors with high power consumption. This classification would affect the pricing structures available to facilities that house AI computing equipment. 

The document also recommends implementing zonal power pricing in areas close to renewable energy generation sites, a model that operates in several European markets.

Grid capacity represents a constraint on data centre expansion in the UK. The report references the government's target of delivering 10GW of AI-related power capacity by 2030, which will require upgrades to transmission infrastructure. Kao Data operates facilities in Harlow that provide capacity for AI workloads, giving the company operational experience with the power demands of machine learning infrastructure.

Kao Data proposes copyright framework changes

The report addresses UK copyright law as it applies to AI training data. Current legislation requires licensing agreements for copyrighted material used in machine learning systems. The technology industry has argued that these requirements place UK facilities at a disadvantage compared to jurisdictions with broader fair use provisions.

Kao Data's recommendations propose changes to copyright frameworks that would maintain protections for creative industries while accommodating the data access requirements of AI training. The report suggests that the UK could implement a system that balances rights holder interests with the operational needs of AI developers.

"Britain possesses extraordinary advantages, world-leading research institutions, exceptional engineering talent, and now substantial investment to back the country's AI ambitions," Spencer Lamb says. "By working in partnership with government, we believe we can transform these strengths into the physical infrastructure that will power the next generation of industrial-scale AI innovations and deliver solutions that position the UK at the forefront of the global AI race."

In the report is the examination of AI Growth Zones, designated areas where the government plans to concentrate AI infrastructure development. Kao Data recommends structures that would align public sector planning decisions with private sector deployment timelines. 

The report suggests that coordination between infrastructure programmes and investment commitments will determine whether the UK can deliver capacity at the pace required by technology companies.

Recommendations from within the report draw on the company's experience developing and operating data centres that house AI computing equipment. Kao Data's facilities in Harlow provide capacity for machine learning workloads, which have different power and cooling requirements compared to traditional data centre applications.

"Our new report offers a practical roadmap to make this happen, drawing on our experience developing data centres, engineered for AI and advanced computing, and operating those which already power some of the world's most demanding workloads," Spencer says.