Why the next wave of electricity demand is a strategic issue for the nuclear industry

Electricity demand is entering a new phase. Not a gradual increase, not a cyclical rebound, but a structural shift driven by the rapid expansion of data centres and artificial intelligence workloads. For the nuclear industry, this evolution is not peripheral. It goes to the heart of how future capacity is planned, financed, regulated and integrated into energy systems.

What is emerging is not simply a question of “how to power AI”, but a broader challenge: how to align long-term, capital-intensive nuclear assets with a form of electricity demand that is growing fast, operating continuously, and increasingly strategic for national economies.

For nuclear stakeholders, this moment calls for strategic clarity rather than technological debate.

When digital growth becomes baseload demand

AI is often framed as a software revolution. In reality, it is a physical one. Large-scale model training and inference rely on vast data-centre infrastructures that operate around the clock. These facilities are not flexible loads. They require continuous power, extremely high reliability, and predictable long-term supply.

Energy system planners are now confronting projections that show global data-centre electricity consumption approaching twice today’s levels by the end of the decade, driven by AI. In several advanced economies, expected growth in data centre demand alone rivals or exceeds historical annual increases in total electricity consumption.

This matters because it changes the nature of demand. Unlike electrification of transport or heating, which introduces variability and behavioural elasticity, AI-driven data centres behave much more like industrial baseload. They do not follow daily or seasonal cycles. They do not tolerate curtailment. And they increasingly influence where generation assets are built.

For the nuclear industry, this represents a rare alignment between demand characteristics and nuclear power’s core strengths.

Why energy systems are struggling to absorb this shift

Today’s energy systems were not designed for this growth profile. Variable renewables continue to scale rapidly, but their intermittency creates challenges when matched with 24/7, non-interruptible demand. Natural gas offers dispatchability, yet raises long-term questions around emissions exposure, fuel price volatility and geopolitical dependence. Grid reinforcement alone is proving slower and more capital-intensive than many governments and utilities anticipated.

As a result, data centre operators, utilities and policymakers are moving beyond short-term power procurement and into infrastructure strategy. Power supply is no longer treated as a marginal cost of digital expansion, but as a determinant of competitiveness, resilience and sovereignty.

It is in this context that nuclear power is returning to strategic discussions, not as an ideological choice, but as an infrastructure option whose attributes match emerging system needs.

Nuclear power as a strategic infrastructure asset

Nuclear energy’s relevance to data centre growth lies less in innovation narratives than in fundamentals. High capacity factors, long asset lifetimes, low operational emissions and predictable output make nuclear uniquely suited to serve continuous, large-scale demand.

This logic is increasingly reflected in market signals. Nuclear assets are being re-evaluated not only as electricity generators but also as anchors of regional energy systems. Interest from technology companies in long-term nuclear offtake, including through existing plants, life-extension projects, and, prospectively, new builds, reflects a broader recognition: stable power is becoming a strategic input to digital economies.

At the same time, expectations remain realistic. Nuclear alone cannot meet the entire growth in data centre demand, nor can capacity be deployed overnight. Large reactors, small modular reactors and life-extension programmes all come with distinct timelines, regulatory pathways and risk profiles. The strategic question is therefore not whether nuclear “wins”, but how nuclear fits into a diversified, resilient energy system designed for the next thirty to fifty years.

The core issue is not technology but decision architecture

For nuclear stakeholders, the most difficult challenges raised by AI-driven demand are not technical. They are structural.

How should new nuclear capacity be sited when demand is geographically concentrated but grids are constrained? How should ownership and offtake models evolve when customers seek long-term certainty but assets operate over several decades? How do regulators adapt frameworks designed for centralised generation to new configurations such as co-location, dedicated supply or hybrid public-private models?

These questions cut across energy policy, industrial strategy, finance and governance. They require coordination between actors with different incentives, time horizons and risk tolerances. They also demand a level of strategic integration that the nuclear sector, historically segmented between policy, engineering, operations and finance, is still adapting to.

This is where the role of strategic nuclear advisory becomes critical.

What this means for nuclear leaders

For utilities, the rise of AI-driven demand introduces new customer archetypes: fewer in number, larger in scale, and far more strategic than traditional industrial loads. For governments, it reinforces the link between nuclear policy and economic competitiveness. For investors and developers, it reshapes the risk-return profile of long-term nuclear assets.

Responding effectively requires more than incremental optimisation. It requires clear strategic choices, robust operating models, and delivery frameworks capable of performing over long lifecycles in evolving contexts.

At Damona, we work with nuclear stakeholders precisely on these challenges. Our focus is not on promoting technology, but on supporting clarity in complex decisions: aligning strategy with regulatory reality, structuring operating models for long-term performance, shaping industrial and supply-chain strategies, and supporting disciplined capital project delivery.

AI is accelerating change in electricity demand. Nuclear power is increasingly part of the strategic response. The decisive factor, however, will be how well organisations connect ambition to execution.

For the nuclear industry, this is not a disruption to fear. It is a strategic moment to shape the next phase of its role in the global energy system.