Pragmatism and the AI Boom

There has been much discussion recently as to whether the current AI boom is actually an AI bubble. With such uncertainty and volatility prevalent in the market, the data centre industry must carefully navigate a clear but challenging opportunity.

The builders and operators of data infrastructure, and especially data centres, face a range of challenges as they must navigate the rising demand of a technological wave that will be a critical part of Europe’s competitive and sovereign future, but one that is also far from predictable.

AI Data Centre Investment and Capital Surge

The current AI boom has seen investment in data infrastructure soar. Data centres designed for AI workloads are projected to require £3.8 trillion ($5.2 trillion) in capital expenditure, compared to £1.1 trillion ($1.5 trillion) for those powering traditional IT applications. Almost two-thirds (62%) of strategy leaders noted that an overburdened legacy operating model cannot support current and future strategic objectives and plans, according to Gartner.

However, even as providers scramble to meet demand, the Moody’s Ratings report of 2024 has warned of the dangers of overcapacity. As a result, hyperscalers are constantly revising capacity plans to cater to uncertain needs. AI infrastructure investment is already greater than other comparable scale-outs in the past, increasing risk. The State of European Data Centres 2026 report (SoEDC 2026) found that data centre construction and installation Investments for hyperscale-owned facilities would average around €7 billion (£6 million) per year to 2031. The ratings agency warns that existing finance vehicles may need to be adapted to be more suited for AI investments.

AI Infrastructure Volatility and Overcapacity Risk

Another issue to highlight in this context is that AI technology and adoption have not gone entirely smoothly or predictably. There have been significant instances of overinvestment and deployment that have had to be rolled back as they have not produced the value expected. Examples such as Johnson and Johnson, and various rehirings after AI failures have seen much coverage.

Furthermore, the emergence of DeepSeek, and developments by the Ant Group have shown that upstarts and disruptors can significantly affect market and general perceptions, with implications for share prices, valuations, and roadmaps.

Lessons from Previous Technology Scale-Out Cycles

It is said that while history may not repeat itself, on occasion it rhymes. The data infrastructure industry has navigated previous disruptive waves of technology, with crashes and disruption, and learned lessons from them.

From the rise of the internet and the client-server model to the development of as-a-service offerings, server virtualisation and the birth of cloud computing, a surge in demand must be met with a pragmatic, systematic response that looks over the lifecycle and lifespan of the required investments, anticipating and designing in flexibility to accommodate expansion or contraction.

Already, the emergence of neocloud providers, offering bespoke AI and HPC-optimised solutions, such as Coreweave, Global AI, and Nebius, has shown that the industry is agile and adaptable. Forrester and JLL both cite necloud development as a key trend for the near future. More specialist platforms and service providers are likely to emerge in the same manner as specific cloud platforms to support industry verticals and sectors emerged in the recent past.

The SoEDC 2026 report confirms that neocloud providers reinforce the AI market momentum.

“Their focus on ultra-high-density compute, rapid deployment capability and large power tranches aligns with the needs of AI developers, global model providers and emerging cloud-adjacent platforms,” said the report.

Neocloud Providers and AI Factory Expansion

From long experience, data infrastructure builders and operators must carefully consider demand and build accordingly. Taking into account the volatility in technological development and operation, they must also work carefully not to stymy development by being too slow or too sparse with capacity.

Phased and modular builds, with extensive use of prefabricated infrastructure based on reference and pre-certified designs, in conjunction with key partners, from the silicon foundries to server manufacturers and all supporting equipment, ensure that demand can be met in a way that can scale with minimum risk, both up and down. These considerations must be made for ever larger facilities with expected lifespans of up to 20 years.

AI Data Centre Power Demand and Energy Constraints

A key issue in this wave of technology is power – AI is power-intensive.

The Moody’s report highlights that AI data centres are increasingly being built as massive campus-style AI factories with 1-5 GW of power capacity. Data centre rack density has doubled since 2016, with new AI installations exceeding 200 kW per rack.

According to the SoEDC 2026 report, “The expansion of IT power supply across Europe highlights the ongoing structural shift toward larger and more power-dense facilities. In 2024, total colocation IT power reached 7.6 GW, with scale sites to grow at an expected 27% CAGR toward 2031.”

Data centres are increasingly under pressure not only to employ low or no carbon power sources to maintain emissions commitments, but also to generate more themselves to relieve stress on grids in constrained areas.

The ability to achieve this generative capacity varies with region and geography. In areas with abundant renewables available for long periods, such as storage-augmented wind and solar farms, this can be a practical approach. In areas of greater population density and more temperate climates, it may not. Southern Europe shows a strong forward trajectory, driven by Portugal, Spain and Italy, which together move from 682MW in 2024 towards around 5.9GW by 2031, representing a 36% CAGR.