Zonal Pricing and the AI Gold Rush: Who Wins, Who Loses?

The future of AI in the UK might not be decided in London, Cambridge, or Manchester but in the remote and windswept landscapes of Scotland. Tech giants Amazon and OpenAI are pushing for a radical overhaul of Britain’s electricity market—one that could reshape the geography of energy-intensive industries. The proposal? Zonal pricing, a system where electricity costs vary by region, making energy cheaper where it’s abundant and more expensive where supply is constrained.

At first glance, this seems like a straightforward economic argument: let the market reflect real supply and demand conditions more accurately. If wind-rich Scotland can produce electricity at low cost, why shouldn’t AI datacentres flock there to take advantage of it? But as always in economics, incentives create winners and losers, and the implications of such a shift could reverberate far beyond the tech industry.

The Economics of Zonal Pricing: Efficiency vs. Equity

The UK currently operates a single national electricity price, meaning businesses and households across the country pay roughly the same rate regardless of where they are. In contrast, zonal pricing—already used in parts of Europe and the US—would introduce regional price variations.

The potential benefits are clear:

• Encouraging investment where energy is cheapest – Scotland, with its abundance of wind power, could become a hub for energy-intensive industries like AI and cloud computing.
• Reducing waste – Wind farms in remote areas are often forced to shut down due to insufficient local demand and limited grid capacity. Zonal pricing could ensure that electricity is used more efficiently.
• Regional economic development – AI datacentres and other power-hungry industries could bring jobs and investment to parts of the UK outside the traditional economic centres of London and the South East.

However, the economic risks are just as significant:

• Higher costs for businesses in the South and industrial heartlands – If energy-intensive firms in the Midlands or the South of England face higher electricity prices, they may relocate—or worse, shut down.
• Distorting investment in renewables – Companies planning to build offshore wind farms or solar projects could face lower returns in some regions, potentially discouraging investment in clean energy.
• Inequality in household energy bills – If regional electricity pricing extends to consumers, it could lead to a postcode lottery where some households pay far more for power than others.

The battle over electricity pricing is, at its core, a debate about market efficiency vs. equity. Should electricity costs be purely dictated by local supply and demand, or should they be smoothed out to ensure fairness?

AI and Energy: A High-Stakes Relationship

AI, for all its promise, is an energy guzzler. Large language models, such as those developed by OpenAI, require vast amounts of computational power, leading to skyrocketing electricity demands. A single AI data centre can consume as much energy as a small city.

This reality raises deeper questions about the UK’s energy security and net-zero ambitions. The government has committed to phasing out fossil fuels from the power system by 2035, meaning the UK will need an unprecedented expansion in wind, solar, and nuclear capacity. If AI datacentres accelerate electricity demand, will clean energy keep up? Or will Britain be forced to extend the life of gas-fired power stations, undermining its climate targets?

Proponents argue that AI datacentres could drive investment in renewables—after all, cheap, abundant electricity is in the interest of tech companies too. But critics worry that prioritizing AI’s energy needs could divert resources away from households and traditional industries, exacerbating regional inequalities.

The Role of Government: Market Reforms or Market Distortions?

The UK government is currently consulting on the future of the electricity market, with zonal pricing being one of the most contentious proposals. Policymakers face a difficult balancing act:

• If they embrace zonal pricing, they could stimulate regional investment but risk economic dislocation in areas with higher energy prices.
• If they reject it, they may discourage AI-driven growth but maintain a more predictable and equitable energy landscape.

Moreover, the government’s plan to allow small modular nuclear reactors (SMRs) outside traditional nuclear zonescould provide a compromise solution—ensuring datacentres in the South have access to reliable, low-carbon power. But nuclear projects take years to develop, and in the short term, high energy costs remain a major concern.

The Bigger Picture: A Global AI Arms Race

There’s also an international dimension to this debate. The UK isn’t the only country vying to become an AI superpower. The US, China, and the EU are all aggressively expanding AI infrastructure, and energy costs play a huge role in where companies choose to invest.

If the UK’s electricity prices remain among the highest in the world, will AI firms take their business elsewhere? And if Britain pursues aggressive reforms to attract AI investment, will that come at the cost of energy affordability for the wider economy?

These are the economic trade-offs policymakers must grapple with in the coming months. AI’s future in Britain is not just about computing power—it’s about who pays for it and at what cost.

Glossary of Economic Terms

Zonal Pricing: A system where electricity prices vary by region, reflecting local supply and demand.

Market Efficiency: A situation where resources are allocated in the most productive way, minimizing waste and maximizing output.

Equity vs. Efficiency Trade-Off: The balance between ensuring fair economic outcomes (equity) and maximizing productivity and growth (efficiency).

Renewable Energy Investment: Spending on wind, solar, and other clean energy sources to expand capacity and reduce reliance on fossil fuels.

Energy Security: The availability of reliable and affordable energy supplies for households and businesses.

Artificial Intelligence (AI) Infrastructure: The physical and digital systems (e.g., data centres, computing clusters) required to support AI development and deployment.

Economic Incentives: Factors that motivate individuals and businesses to make certain economic decisions, such as investing in regions with lower energy costs.

Industrial Electricity Pricing: The cost of electricity for businesses, which affects investment decisions and competitiveness.

Net-Zero Target: The UK’s commitment to reducing greenhouse gas emissions to net zero by 2050, requiring a major shift to renewable energy.

Small Modular Reactors (SMRs): A new generation of nuclear power plants that are smaller and can be built in a wider range of locations than traditional reactors.

Graham Watson's insight:

This is an interesting story and looks at how the market for electricity might be altered by a switch in the pricing model, from a national market to regional markets.

It's thought that the move could encourage significant consumers of electricity - such as data centres - to move to remoter areas to take advantage of cheaper power. Of course, the flip side is that it will alter incentives in the market for electricity generation, reducing returns to investment in renewables in these locations too.