‘AI regulation is key to Labour’s climate credibility’

Last week, Ofgem revealed that proposed AI datacentres could require more electricity than the UK currently consumes at peak demand. This raises an environmental problem for the Labour government, who want to make the UK a global AI powerhouse. Senior regulators have already warned that there is a lack of coordination around AI’s rapid advance. They must now confront another issue: its environmental regulation. 

The government’s enthusiasm is understandable. AI has become a central part of Labour’s mission for economic renewal. There is evident political will, with the AI Opportunities Action Plan, the creation of AI Growth Zones, and the forthcoming Sovereign AI Unit all representing promising developments.

But, as has been clear for some time, the rise in energy and natural resource consumption will be significant. Nearly two years ago, John Pettigrew, then CEO of National Grid, warned of a six-fold increase in commercial datacentre demand over the next decade. Without regulatory action, Labour’s long-term commitment to reaching net zero is at risk.

Research published by the Centre for Climate Engagement (CCE) at the University of Cambridge identifies this risk to climate targets as a defining governance challenge for governments around the world, particularly where those targets are legally binding, as in the UK.

CCE’s working paper, Regulating the AI-Climate Nexus, maps the global legislative landscape for AI and climate change, finding limited examples of legislation that specifically address its environmental impacts. Most existing AI policy sets procedural obligations and facilitates voluntary and industry-led standards. The focus on environmental impact within these is insufficient relative to the pace and scale of AI infrastructure expansion, demanding serious, evidence-based policy attention. 

As evident in other areas of climate policy, reliance on industry self-regulation or voluntary standards alone can create a fragmented regulatory landscape, harming both environmental goals and business certainty. 

That attention is yet to materialise in the UK and regulators want direction. In February, senior figures from the EHRC, ICO, and Ofcom told the Joint Committee on Human Rights that the Government’s current reliance on sector regulators with overlapping and sometimes conflicting remits risks falling behind fast-moving AI development. Importantly, none of the existing watchdogs has a specific mandate to oversee AI, let alone its environmental impacts. 

Labour has set itself two goals that are potentially on a collision course: it wants to be an international leader in AI development whilst reaching net zero. But these aims can align. Policies like mandatory environmental disclosure for large AI infrastructure projects and binding renewable energy sourcing obligations for datacentres would begin to tackle existing energy and grid capacity issues, and could drive stronger demand for and investment in renewable energy. Stronger coordination and greater clarity by digital, energy and environmental regulators will aid businesses making long-term infrastructure investments. In an area characterised by its unpredictability, public trust would benefit too.

But the window for getting ahead of the problem is closing. Decisions made now on datacentre location, grid connection, and energy sourcing will lock in demand profiles well into the next decade. The launch of the Sovereign AI Unit in April is an opportunity for Labour to provide a strong signal for its plans to reconcile building a world-class AI sector with protecting the UK’s net zero pathway and progressing the clean energy transition.

Labour promised to be a party that governs for the long term; on AI and the environment, that promise is now being tested.

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