AI’s Growth Creates a New Energy Challenge
The conversation around AI often focuses on computing power generation and generation capacity. But the real bottleneck may be far more fundamental: access to reliable, sustainable electricity.
In just a few years, data centers have evolved from large but predictable IT loads to dynamic, power-hungry AI hubs shaping how entire grid systems are planned and operated. As AI accelerates, data centers are becoming one of the major considerations in shaping the future of energy. This is a structural shift. We are seeing the emergence of data center campuses that require gigawatt-scale connections, where just five years ago, a 100 MW facility would have been considered a giant. The scale and complexity of AI demand in particular is changing the game, not just for operators and developers, but for utilities, regulators, and energy infrastructure providers.
In the United States, data center electricity consumption is projected to double or even triple by 2028 compared to 2023 levels. As demand grows at this scale, data centers are becoming an increasingly important consideration in grid planning, highlighting the need for more flexible and resilient energy infrastructure.
The Rise of AI Factories and Why Traditional Grid Planning Is No Longer Enough
The surge in demand driven by AI is unlike anything the sector has experienced before. In many conversations, we are talking less about "data centers" and more about "AI factories", reflecting the scale and intensity of these facilities.
What makes this different from past growth cycles is not just the volume of power required, but the nature of that demand. AI workloads can behave very differently from traditional cloud applications. They are more compute-intensive, place greater demands on cooling systems, and create increasingly dynamic load profiles. Perhaps most critically, the power load patterns are far more unpredictable.
In this context, a power system built for predictability and baseload planning is no longer fit for this purpose. Instead, we must plan around fast-moving, high-density, intermittently peaking loads that may behave more like industrial machines than traditional server farms.
Energy Availability Has Emerged as the Industry’s Greatest Constraint
In many markets, developers can secure capital, land, connectivity, and talent, but not the grid capacity needed within a required timeframe. As a result, data centers can no longer be viewed simply as consumers of electricity. Operators, utilities, and infrastructure providers must work together earlier in the planning process to embed flexibility through solutions such as energy storage, on-site generation, and intelligent load management.
To accelerate capacity delivery and reduce land use, modular, prefabricated substations are being deployed, with integrated gas-insulated switchgear and compact transformers. These solutions are not only faster to deliver, but inherently more flexible and scalable.
Consider Castlebagot in Ireland. In one of Europe’s most grid-constrained regions, a compact substation was delivered to support a hyperscale campus, enabling the grid connection despite land constraints and tight deployment timelines. This project represented a key milestone, necessitating a complete rethink of the grid design toolkit. And it demonstrated what is possible when grid and site planning are considered in parallel from the outset.
This approach is now being adapted across projects in the US, Europe, and Asia, especially in urbanized regions or where traditional grid buildouts are too slow or costly to deliver.
Enabling Flexibility Through Integration and Digitalization
AI and data centers are often viewed primarily as consumers of power. Yet, when designed with flexibility in mind, they can also play an active role in supporting the grid. Combining behind-the-meter generation, battery energy storage systems (BESS), and intelligent energy management can help operators improve reliability, and reduce dependence on the grid as well as enhance continuity by providing seamless power during grid outages.
Digitalization is what makes this possible. Intelligent systems are no longer simply delivering power - they are optimizing it. Real-time data, predictive analytics, and digitally connected equipment enable operators to align energy consumption with grid conditions.
In Finland for example, the recaptured waste heat from a data center’s cooling process is redirected into the local district heating system, cutting emissions and lowering local heating bills. Such a form of whole-system integration is increasingly becoming the norm and a feature of modern digital infrastructure.
This shift is also driving greater integration between the energy and IT sectors, which have traditionally operated independently. Today, resilient infrastructure depends on collaboration across both domains.
Digitalization Is the Enabler of Resilience
Just as AI is revolutionizing what is possible in software and services, it is also reshaping the way we operate infrastructure.
Intelligent systems are not just delivering power - they are optimizing it. From smart transformers to digitally monitored switchgear and predictive analytics for maintenance and operations, real-time data and decision-making is being embedded into every part of the energy value chain.
We have reached the moment where the effective collection, analysis, and application of data is as important in energy as it has been in IT.
Digitalization is what enables flexibility. It helps data centers shift loads, align compute with renewable energy availability, and coordinate with grid conditions in real time.
The Path Forward
The future trajectory of AI, data centers, and power systems remains uncertain. We do not yet know how quickly AI demand will grow, where it will concentrate, or how technology and regulation will evolve. While this remains uncertain, building flexibility into infrastructure provides a foundation for reliability, sustainability, and long term adaptability. The path forward is a future-ready strategy.
In an era of transformation, building flexible infrastructure is how we stay resilient. It’s how we protect the grid. And it’s how we ensure that AI and digital services can continue to grow - without leaving sustainability behind.
