AI expansion triggers global race for power and real estate

Artificial intelligence growth is outpacing the world's ability to build the physical infrastructure it relies on, according to new analysis from investment and advisory firm Heligan Group.

The firm's latest AI infrastructure study identifies power, land, and cooling as the primary constraints on the expansion of AI workloads. It argues that the limiting factor in the sector is shifting away from chips and towards the data centres that provide the necessary electricity, space, and thermal management.

"As hyperscalers push past historic investment levels and model sizes continue to accelerate, the physical layer of AI infrastructure has become the limiting factor to global innovation. A single NVIDIA H100 draws up to 1,000 watts; racks exceed 100 kW. This is no longer a race for silicon - it's a battle for grid access, land and engineering capability," said Andrew Dickinson, Head of Infrastructure Services, Heligan Group.

Heligan links rapid AI adoption with record spending on large-scale computing facilities. It forecasts that global data centre mergers and acquisitions will exceed USD $80 billion in 2025. It also expects hyperscale cloud and technology companies to invest around USD $400 billion this year in securing power-ready capacity.

"AWS recent commitment to invest up to $50 billion to AI and supercomputing infrastructure for the U.S. government is a perfect example: the global AI arms race is shifting from chips to the physical systems that power, cool and house them. For investors, the opportunity lies in platforms that can deliver power, cooling and scalability at speed."

The report describes a market in which scale transactions are becoming more common. Deals exceeding $10 billion are described as "routine" as buyers seek platforms capable of expanding power delivery and adapting existing buildings.

Dickinson stated that this consolidation is driven by strategic intent, with deals exceeding $10 billion now considered routine. AI workloads are fundamentally redefining infrastructure requirements; as a result, platforms are no longer valued solely on installed capacity. Instead, valuations are now predicated on expandable megawatts, retrofir potential and proximity to reliable power.

"The engineering layer of data-centre design is also becoming a decisive competitive advantage. Where legacy data centres were engineered for predictable loads, AI demands thermally intense, rapidly scaling environments. Cooling is shifting from traditional air to liquid loops, immersion tanks, and submerged modules. Some operators are even experimenting with offshore locations and deep-sea water for thermal efficiency."

Dickinson said the way power is brought into and distributed across facilities is also changing as operators adapt to higher densities and regulatory pressure.

"Power architecture is evolving alongside this. Vertical substations, on-site generation, and dynamic load balancing are replacing legacy cabling and redundancy systems. The most valuable platforms are built to retrofit and reconfigure for changing chip designs, sustainability mandates, and regulation."

Grid strain

Heligan notes that electricity networks are struggling to keep up with demand in several established hubs. It highlights grid strain and planning delays as major factors in project delivery for new data centres.

The analysis points to moratoria in markets such as Northern Virginia, Dublin and Frankfurt. It states that construction lead times are now longer than five years in many regions.

"Energy access, permitting and build viability now outrank tenant demand. With cooling accounting for up to 40% of total energy use, investors are targeting platforms with waste‐heat recovery, district heating, and renewable baseloads. The ability to demonstrate low‐carbon delivery is emerging as a pricing premium."

The report says that these pressures are changing how investors and operators value assets. Sites with access to robust electricity connections, lower-carbon power sources and permissions in place are gaining attention.

UK pipeline

Despite global constraints, Heligan identifies the UK as an emerging leader in AI-ready infrastructure. It cites a national project pipeline now exceeding GBP £36 billion and forecasts that power capacity dedicated to data centres could reach 6 GW by 2030 under the government's Compute Roadmap.

The UK is highlighted as a standout market, with a data centre pipeline now exceeding £36 billion and power capacity forecast to reach 6 GW by 2030 under the government's Compute Roadmap.

"UK engineering and construction firms are rapidly expanding to meet hyperscale demand, delivering modular builds, advanced cooling systems and grid-adjacent campuses. his positions the UK as Europe's most competitive market for AI infrastructure, with hyperscale campuses anchoring long-term growth."

 Dickinson said the ability to adapt data centres over time is becoming a core part of how investors judge future value.

"AI's expansion is no longer defined by chips; it is constrained by infrastructure. Control of physical systems is now driving competitive edge, and the winners will be those who can build, power, and cool at speed."

Dickinson noted that the UK possesses the momentum, engineering depth, and policy alignment required to anchor the next decade of global AI capacity. He stated that investment activity is expected to focus on securing megawatts and acquiring ownership of the platforms that power intelligence. According to Dickinson, the most valuable assets will be those designed to reconfigure in response to evolving chip designs, sustainability mandates, and regulatory pressure.

Dickinson's assessment highlights a fundamental shift in the AI landscape: the focus has moved from software innovation to physical resilience.