The race for AI leadership has largely been framed as a contest for the best chips, models and talent up until now. But behind every algorithm, model, query, and breakthrough is the energy that powers it all.
As AI moves from R&D into living rooms, workplaces, and factories, access to reliable electricity and the speed at which data centers can connect to the grid (AKA “time to power”) is becoming the defining factor determining where data centers (or AI factories) get built and who gets to reap the economic benefits.
EVP Energy Management, Schneider Electric.
For investors, it is no longer enough for a country to promise abundant electricity in the future.
Power must be accessible, predictable, competitively priced, and available on a timeline that matches the speed of the AI market.
A connection delayed by several years can mean missing an entire technology cycle.
Three factors that will shape where AI investment lands
Data center operators make investment decisions based on three fundamentals: regulatory environment, availability of energy and the price of that energy.
Increasingly, however, investors are seeking confidence: confidence that permits will be secured and grid connections delivered on schedule, and power will remain affordable.
China and the US dominate global capacity but are taking different paths. China is investing around US$295 billion in a nationwide AI computing network, alongside energy infrastructure and renewables. In the US, growing electricity demand and evolving grid-connection timelines are increasing interest in on-site generation and storage.
Europe presents a more fragmented picture. Some markets offer available capacity and attractive investment conditions; others face grid queues and complex permitting. In spite of this, Europe has many of the right ingredients. Its mix of nuclear power and renewables, combined with established infrastructure and deep industrial expertise, should make it a natural home for the next generation of AI infrastructure.
Europe may have missed much of the first wave of AI data center build out, but it still has the opportunity to capture the economic benefits of the next one. With targeted investment and smarter energy policy, countries can still reshape the map of AI infrastructure investment.
There are three levers the world should pull now to capitalize the powerful impact AI can have.
1. In the AI economy, speed is power
Energy systems around the world are struggling to accommodate rapid growth in electricity demand. Many of today’s grids weren’t built to manage such a diverse mix of energy sources alongside increasingly intense and concentrated power demand. As such, an estimated 2,500GW of generation capacity is waiting in connection queues worldwide.
In Europe’s data center hubs, often referred to as FLAP-D (Frankfurt, London, Amsterdam, Paris, and Dublin), data centers can wait up to a decade for a grid connection, while a facility may take just four years to build.
Governments and grid operators must accelerate permitting and connection processes. There needs to be more transparency around expected grid connection timelines, supported by delivery milestones and regular reporting so developers and investors can plan with greater certainty. It also means moving from “first come, first served” to “first ready, first connected”, prioritizing viable, grid-supportive projects over speculative applications.
UK efforts to remove these “zombie projects” demonstrate how queue reform can shorten waiting times and strengthen investor confidence. This helped shrink waiting times which were up to 15-years for some projects.
2. Flexibility is the fastest source of new capacity
Grid modernization is essential, but major upgrades could take up to 15 years. While wider grid expansion takes place, flexibility can free up existing capacity more quickly.
In many regions, the challenge is not simply how much electricity is generated, but whether it is available where and when it is needed. Energy-management technologies give operators the visibility and control to optimize energy use across buildings, transport and industry.
They can shift non-critical demand, such as heating, cooling and EV charging, away from peak periods. Battery storage complements this by storing lower-cost or surplus electricity for use when demand is highest. As these capabilities become more widely connected and coordinated, they could unlock greater grid capacity, reliability and flexibility at scale.
Data centers themselves can also become active grid assets through intelligent energy management. If European data centers offered just 30 hours of flexibility per year, the grid capacity available to them could more than double. The technologies needed to achieve this already exist, including digital energy-management systems, battery storage and microgrids.
Compass Data centers offers an early example of what this can look like in practice.
Schneider Electric has already delivered around 150 prefabricated modular data center solutions for Compass, while connected, condition-based maintenance has helped reduce manual on-site interventions by 40% and operating expenditure by 20%.
Alongside microgrid controls being deployed at its Phoenix campus, this shows how data centers can scale more predictably while gaining the visibility and control to manage power dynamically when the grid is under pressure.
Countries now need the right incentives and market mechanisms to reward flexibility and make participation commercially viable.
3. Make flexibility the path to cheapest power
Technology can make energy flexible, but economics will determine whether that flexibility scales. In regions like France, Germany, Italy and the Nordics where grid flexibility exists, households and businesses can be rewarded for using power when renewables are plentiful and reducing demand at peak times.
Flexibility in data centers could mean lower tariffs or faster staged connections in exchange for battery storage, automated demand response and participation in flexibility markets. Real-time monitoring and automated controls can manage these adjustments without compromising performance.
The grid’s largest untapped reserve may not be another power station, but the millions of connected assets already hiding in plain sight.
4. The real race to power AI
AI infrastructure will go where power is available, affordable and resilient. A recent report by Reuters found that European data center developers are moving away from major cities to where energy is cheaper and connections are quicker.
Countries unable to provide those conditions risk losing more than data centers. They could also lose the investment, jobs, industrial ecosystems and innovation that develop around them.
The countries that want to capitalize on the AI boom should be all-in on electricity. That means expanding clean generation, strengthening and digitalizing grids, improving regulatory clarity and unlocking the flexibility inside homes, buildings, transport and industry.
The future of AI will be shaped by data centers. But it will be won where power is abundant, resilient, and affordable. In the AI era, access to electricity becomes access to economic advantage.
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