Key takeaways
- AI infrastructure is colliding with physical constraints, including multi-year grid delays, rising construction costs, water consumption and community opposition.
- New data-centre models are emerging, from modular and floating facilities to power-adjacent campuses, orbital compute and AI-native neoclouds such as Nebius.
- The opportunity extends beyond GPUs and hyperscalers into cooling, energy orchestration, specialised chips, modular construction, security and compute-management software.
AI may live in the cloud, but the cloud is running out of places to live.
Amazon, Microsoft, Alphabet and Meta are preparing to spend approximately $725 billion on capital expenditure in 2026, much of it on data centres, chips and networking. CreditSights estimates that approximately 75% of hyperscaler capital expenditure this year will be directed towards AI infrastructure.
Yet building the next generation of AI infrastructure is becoming surprisingly difficult. Grid connections can take four to eight years, construction costs have risen to more than $11 million per megawatt, communities are objecting to the water and electricity demands, and regulators are beginning to ask who should pay for the strain on local infrastructure.
The industry’s answer is no longer simply to build more enormous warehouses.
Data centres are being squeezed into shipping containers, inserted into former factories and storage facilities, placed beside nuclear and gas power stations, mounted on ships and barges and, if a new generation of founders gets its way, launched into orbit.
The data centre is escaping the building.
This is more than an architectural curiosity. It signals a deeper shift in the AI economy. Compute is becoming constrained not by demand for intelligence, but by electrons, water, grid capacity, cooling and community consent. The companies that solve those physical bottlenecks could capture as much value as the companies building the models.
AI is colliding with the physical world
The International Energy Agency estimates that global data centre electricity consumption will more than double to approximately 945 TWh by 2030, slightly more than Japan consumes today. From 2024 to 2030, data centre electricity demand is expected to grow by approximately 15% a year, more than four times faster than electricity demand from the rest of the economy.
The acceleration is already visible. Global electricity consumption by data centres rose 17% in 2025, while electricity use by AI-focused facilities increased much faster. In the US, data centres consumed approximately 176 TWh in 2023, equivalent to 4.4% of national electricity consumption. The US Department of Energy expects that figure to reach between 325 TWh and 580 TWh by 2028, or 6.7% to 12% of all US electricity.
To put the scale in perspective, a gigawatt data centre campus consumes roughly as much electricity as a large city. The industry is no longer ordering power by the megawatt. The largest planned projects are discussing multiple gigawatts.
But power generation and transmission cannot be expanded at software speed. JLL estimates that the average wait for a US grid connection is now approximately four years. Across Asia-Pacific, connection times can range from 24 months in emerging markets to more than eight years in established hubs.
The buildings are also becoming more expensive. The average global cost of constructing data centre capacity increased from $7.7 million per megawatt in 2020 to $10.7 million in 2025. JLL expects it to rise again to $11.3 million per megawatt in 2026. At that price, a 500 MW campus can imply more than $5 billion of construction expenditure before accounting for the most advanced chips inside it.
Power is only one constraint. A large data centre can consume as much as five million gallons of water a day, depending on its location and cooling design. Recent estimates suggest that AI-related data centres in the US could require up to 32 billion gallons of water annually by 2028.
AI may feel weightless to the user, but its infrastructure is anything but.
The pushback is becoming political
For years, data centre development was treated primarily as a question of zoning, tax incentives and economic development. It is rapidly becoming a political issue.
Communities are asking whether the benefits justify the cost. Data centres create thousands of temporary construction jobs, but relatively few permanent roles once operational. Meanwhile, residents worry about electricity prices, water consumption, diesel backup generators, noise, land use and the tax incentives offered to developers.
In August 2026, Pennsylvania introduced new rules requiring AI data centre developers to meet environmental and transparency standards, consult local communities and demonstrate that projects will not raise electricity prices for residents. The state also removed data centres from its fast-track permitting programme and prohibited state agencies from signing non-disclosure agreements with developers.
The timing is significant. Amazon announced a $20 billion infrastructure investment in Pennsylvania in 2025, but the state is signalling that capital alone will not guarantee approval. A Reuters/Ipsos poll found that only a third of Americans support the current pace of data centre development, while just 14% would welcome a facility in their own community.
Indianapolis has approved a moratorium on new data centre projects through 2027 following significant community opposition. Tucson introduced additional disclosure and conservation requirements for large water users after a proposed data centre raised concerns about consuming hundreds of millions of gallons annually.
The backlash is not confined to the US. Singapore imposed a moratorium on new data centres in 2019 before reopening the market under stricter sustainability requirements. Ireland spent years restricting new grid connections around Dublin and now requires developers to locate in areas with sufficient capacity or provide flexible generation and storage.
PJM Interconnection, the largest US grid operator, has even proposed requiring data centres to switch to backup power during grid emergencies. PJM serves 67 million people and recently fell 6.8 GW short of its reliability requirement.
A new regulatory compact is starting to emerge. Future data centres may be expected to bring their own power, finance grid upgrades, disclose water consumption, support local infrastructure and prove that the economic contribution extends beyond the construction period.
Faced with constraints around power, land, water and community consent, the industry is experimenting with radically different forms of data centre infrastructure.
If the grid cannot move faster, move the data centre
A traditional data centre can take 18 to 24 months to complete, assuming the operator can secure the land, equipment, permits and electricity. That assumption is becoming increasingly heroic.
Containerised data centres offer a different proposition: manufacture the facility in a factory, transport it to wherever capacity is available and add new modules as demand grows. Servers, networking, cooling and power management can all be integrated into a standardised enclosure that looks, from the outside, like a shipping container.
Schneider Electric already offers pre-engineered and pre-tested modular systems combining IT, power and cooling infrastructure. Vertiv, Eaton, Delta and other established infrastructure companies are developing similar products. Omdia expects the prefabricated modular and micro data centre market to reach $11.7 billion by 2027.
The description “data centre in a shipping container” can make the model sound small or temporary. It may be better understood as the industrialisation of data centre construction. Instead of treating every campus as a bespoke real estate project, operators can begin to assemble compute capacity like Lego.
Nano and micro data centres could also move compute closer to where data is created. A containerised facility might sit beside a factory, hospital, telecom tower, defence installation, retail distribution centre or renewable energy project. This could be particularly valuable where latency, resilience, security or data sovereignty makes sending everything to a distant hyperscale campus less attractive.
There are trade-offs. Distributed facilities are harder to manage, provide less capacity at each location and offer fewer opportunities for customisation. But they can be deployed in months rather than years and expanded without committing to the full cost of a large campus upfront.
In a market where grid access and time to compute are increasingly scarce, flexibility has a value of its own.
The hidden value of an old warehouse
Another emerging model is to convert existing buildings into data centres.
Warehouses, factories, storage facilities and other industrial properties are being evaluated not simply for their floor space, but for the infrastructure already connected to them. A former manufacturing plant may have high-capacity electricity connections, a substation, fibre access, secure grounds, loading facilities and industrial zoning.
This does not mean that any empty warehouse can become a data centre. The requirements are significant. Floors must support heavy equipment, cooling systems must be installed, fibre must be available and electricity must be supplied at a level far beyond the needs of a typical logistics facility. In many cases, retrofitting the building will be more expensive than the structure itself.
But where the power infrastructure exists, conversion may still be faster and cheaper than starting from an empty plot. PwC argues that redeveloping industrial sites can shorten data centre development timelines, particularly outside established clusters where both land and grid capacity have become scarce.
Storage spaces are particularly interesting because they are generally large, secure and often close to urban populations. Yet the opportunity is highly selective. A storage building with limited electricity cannot become an AI facility simply because it has available floor space.
The most valuable conversion candidates will be buildings where the electrical connection is worth more than the real estate.
That could create a new kind of property arbitrage. Investors have traditionally valued industrial assets based on location, rent and redevelopment potential. In the AI infrastructure era, the first question may become: how many megawatts can this site access, and how quickly?
Data centres set sail
If land, water and cooling are constraints, one answer is to move the facility onto water.
Nautilus Data Technologies demonstrated the concept with a data centre on a barge in Stockton, California. The facility used naturally cold river water through a closed-loop cooling system, avoiding conventional chillers and cooling towers.
Backblaze, one of the facility’s customers, described a data centre with no air-conditioning ductwork or traditional hot and cold aisles. Heat was instead removed through a system of pipes carrying water cooled by the river outside.
More recently, Samsung Heavy Industries has been developing purpose-built floating data centre vessels, with an initial deployment planned alongside US infrastructure developer Mousterian. Floating facilities could be positioned close to coastal cities, ports, offshore energy generation and submarine cable landing stations.
The logic is compelling. Water can provide more efficient cooling, coastal locations offer connectivity and floating facilities avoid competition for valuable urban land. Barges and ships can potentially be built in specialised shipyards and delivered to a location more quickly than a conventional campus.
There are new risks, including corrosion, maritime regulation, storms, environmental concerns and physical security. Operators must also ensure that heat returned to the surrounding water does not damage local ecosystems.
Floating facilities are unlikely to replace land-based data centres, but they could become an attractive option in land-constrained coastal markets. Pairing a floating data centre with offshore wind or another nearby source of generation could make the model even more interesting.
The cloud, it turns out, may have a maritime layer.
The most ambitious destination is space
Moving data centres onto water sounds radical until you consider the companies planning to launch them into orbit.
Space offers abundant solar energy and avoids competition with terrestrial grids, water systems and local communities. For data already created in space, including satellite imagery and communications, processing the information in orbit could reduce the need to transmit enormous raw datasets back to Earth.
Orbital says it is building the first commercial AI compute infrastructure in low Earth orbit and plans its first launch for 2027. Other companies are working on radiation-resistant processors, orbital edge computing and satellite constellations designed to carry significant compute capacity.
JLL believes orbital systems, if the economics become viable, are more likely to specialise in asynchronous and energy-intensive workloads than compete directly with terrestrial facilities for real-time inference. A scientific workload might tolerate a delay while results are transmitted back to Earth. A consumer waiting for an AI assistant to answer a question probably will not.
The engineering challenges are substantial. Launch costs remain high, hardware cannot easily be repaired, radiation damages electronics and rejecting heat in a vacuum is more difficult than the phrase “cold space” suggests. Communications bandwidth, space debris and regulation present additional obstacles.
For now, data centres in space are a long-term possibility rather than an answer to next year’s grid connection queue. But the fact that credible founders and investors are pursuing the idea says something important about the scale of the terrestrial problem.
When launching servers into orbit begins to sound remotely rational, getting electricity and planning permission on Earth has become too difficult.
Energy companies become AI infrastructure companies
The most important change may be the reversal of a long-standing assumption. Instead of bringing electricity to a data centre, developers are beginning to bring the data centre to the electricity.
Talen Energy developed a data centre campus beside its Susquehanna nuclear facility in Pennsylvania and later sold the site to Amazon Web Services for a reported $650 million. Talen describes it as the world’s first 24/7 carbon-free co-located data centre campus.
In Texas, Constellation subsidiary Calpine has agreed to supply a CyrusOne data centre beside the Freestone Energy Center with 380 MW of power, with a second phase potentially adding another 380 MW. Along with a separate agreement, Constellation has now contracted more than 1.1 GW of data centre power in Texas.
Co-location can reduce transmission requirements, avoid lengthy grid interconnection queues and give operators greater certainty over power supply and pricing. It also turns energy companies into potential data centre developers, landlords and joint-venture partners.
This could prove to be one of the most important shifts in the AI stack. Power station owners control the scarce resource, understand permitting and already know how to finance infrastructure over several decades. Some may decide that selling electricity into the grid is less attractive than selling powered land, data centre capacity or compute directly to technology companies.
Nuclear plants are especially attractive because they provide large quantities of reliable, low-carbon baseload electricity. Natural gas plants offer flexibility and faster development, while solar, wind and geothermal projects could become more valuable when combined with batteries and workloads capable of adjusting to periods of energy availability.
There are unresolved regulatory questions. A data centre consuming power “behind the meter” may avoid certain transmission charges even while relying on the wider grid for backup. Regulators must decide who pays for resilience and whether co-located facilities can remove power that would otherwise serve households and businesses.
Nevertheless, the direction is becoming clear. Data centre location is increasingly determined by available megawatts rather than proximity to large cities.
AI training workloads can tolerate more latency than consumer-facing inference, allowing operators to move energy-intensive compute to wherever electricity is abundant. Energy is no longer one input into data centre site selection. It is becoming the site.
The rise of the AI neocloud
Not every new data centre model is defined by the building. Companies such as Nebius and CoreWeave are changing who finances, assembles and sells AI infrastructure.
Nebius combines owned data centres, leased colocation capacity and infrastructure financed by external partners. In July 2026, the company introduced an asset-light partnership model that allows partner-owned data centres and hardware to join the Nebius capacity pool. Nebius supplies the software platform and customer access without financing every facility itself.
This hybrid approach offers a potential middle ground between owning the entire infrastructure stack and operating purely as a software layer. Nebius can add capacity more quickly, while energy companies, infrastructure funds and data centre operators gain access to its customers and AI cloud platform.
The capital requirements remain enormous. Nebius has just increased a convertible debt offering to $5 billion to finance its data centres and AI platform. It is also investing approximately £1.7 billion in UK capacity, developing a New Jersey facility with up to 300 MW of capacity and operating across Finland, Iceland, the UK, France, Israel and the US.
Demand is supported by unusually large commitments. Nebius has agreed to provide Microsoft with $17.4 billion of AI infrastructure capacity over five years and has signed agreements with Meta that could be worth up to $27 billion.
The neocloud model effectively turns GPUs, power contracts and data centre capacity into a new financial asset class. It can scale faster than a conventional cloud provider, but it also introduces significant financing and utilisation risk. If customer demand or GPU economics change, these companies remain responsible for expensive, rapidly depreciating infrastructure.
The chip could replace the next building
Data centres are not only changing location. They are also being redesigned from the inside out.
More specialised chips could reduce the electricity, cooling and floor space required to produce a given amount of compute. Etched is developing Sohu, an application-specific chip built specifically for transformer models. Unlike a general-purpose GPU that can support many types of workloads, Sohu sacrifices flexibility in pursuit of greater inference performance and energy efficiency.
Etched has now raised hundreds of millions of dollars, secured more than $1 billion in customer contracts and reached a reported valuation of $21 billion. Its claims still need to be proven at scale, and the semiconductor industry is full of technically impressive challengers that failed commercially. But the company represents an important shift towards measuring infrastructure by useful computation rather than the number of chips or megawatts deployed.
If specialised silicon can deliver significantly more tokens per watt, the impact will be felt far beyond the chip market. It could reduce how many new data centres need to be built.
Cooling is undergoing a similar transition. AI racks are becoming too dense for conventional air cooling, accelerating the move towards direct-to-chip and immersion systems. Israeli company ZutaCore raised $100 million in June 2026 from Mitsubishi Electric, Carrier and Samsung to expand its waterless, two-phase liquid cooling technology.
ZutaCore’s sealed system removes heat directly from processors and, according to the company, can reduce cooling energy consumption by up to 82% while supporting much higher computing density.
This highlights an important Israeli opportunity. Israel is unlikely to compete with the US, China or Gulf states in financing enormous data centre campuses. But it can build the technologies that make those facilities more efficient, resilient and secure. Cooling, power management, cyber security, physical security, specialised silicon and workload optimisation all play to established Israeli strengths.
The next Israeli data centre success story may never own a data centre. It may simply make every data centre perform better.
The data centre becomes a product
These emerging models should not be viewed as mutually exclusive.
A future AI facility could be manufactured from prefabricated modules, installed on a former industrial site, connected directly to a power station, cooled through a closed-loop liquid system and filled with specialised inference chips. Smaller versions could sit close to factories, hospitals or population centres, while energy-intensive training workloads move to remote regions with plentiful electricity.
Over time, floating and orbital facilities may add further layers to this system.
The bigger shift is conceptual. The data centre is moving from a relatively standardised real estate asset to a configurable industrial product. Location, construction method, chip architecture, cooling technology, power source and workload can all be optimised together.
This expands the investment opportunity far beyond building another cloud provider. The picks and shovels include modular construction, transformers, batteries, microgrids, power electronics, liquid cooling, specialised chips, fibre, water management, workload scheduling, physical security and tools that help operators comply with rapidly evolving regulations.
There may also be an important new software layer. As compute becomes distributed across hyperscale campuses, shipping containers, converted industrial sites and privately powered clusters, workloads will need to be directed according to price, latency, availability, security, carbon intensity and regulatory constraints.
The equivalent of an air traffic control system for compute could become a valuable category in its own right.
The next AI bottlenecks are physical
The AI infrastructure boom is often framed as a race to build the largest possible data centres. That may only be the first phase.
The more interesting race is to make compute deployable wherever power, land and political permission can be found. That could mean a container beside a factory, an old warehouse with a valuable grid connection, a cluster next to a nuclear plant, a barge outside a coastal city or, eventually, a satellite powered by uninterrupted sunlight.
Hyperscalers will continue building enormous campuses. The scale of demand leaves them little choice. But the assumption that the future of compute is simply more of the same building, constructed in more places, is starting to look incomplete.
For founders and investors, the opportunity lies in recognising that the data centre is becoming less like a building and more like a supply chain. Every constraint creates a potential new category: electricity scarcity creates energy orchestration, water scarcity creates new cooling systems, slow construction creates modular facilities, community opposition creates compliance and transparency tools, and expensive general-purpose hardware creates demand for specialised chips.
AI may be built in software, but its next bottlenecks are stubbornly physical.
The next great AI infrastructure company may not begin by asking how to build a better model. It may begin by asking where on Earth, or beyond it, we can put the machines.
He is a former General Partner at Google Ventures (GV) in Europe, former head of Google for Entrepreneurs in Europe, and founding head of Campus London, Google's first startup hub. Eze writes on Israeli tech, venture capital, artificial intelligence, and founder strategy.
He is also the founder of Techbikers, a nonprofit that brings together the startup ecosystem on cycling challenges in support of Room to Read.
- The Data Centre Is Escaping the Building - August 20, 2026
- The AI Didn’t Go Rogue. It Followed the Goal. - August 19, 2026
- AI Musical Chairs - August 18, 2026
