The current AI market doesn't add up. US hyperscalers have reportedly taken on $220 billion in debt in the past year. The two leading US frontier AI model makers have not yet shown they can operate profitably. And the US public has begun pushing back against the development of the datacenters needed to fulfill anticipated AI demand.

But plausibility and politics aside, it's unclear where the world will get the electrical power to sustain the imagined AI industry.

Gartner predicts world datacenter power demand will reach 132 GW in 2026, up from 104 GW in 2025, and 290 GW by 2030. Morgan Stanley expects US datacenter demand could go as high as 74 GW by 2028, with a projected shortfall of about 49 GW. 

By 2036, Teravolt, a London-based AI infrastructure company, foresees AI demand requiring 410 GW, a 240 GW shortfall for the 170 GW the biz anticipates will be available from the grid at that time.

Datacenters can be built in one to three years but building out new grid infrastructure takes a lot longer – five to 15 years for planning, permitting, and construction, according to Teravolt. 

As a result, the company contends some AI projects won't happen, some AI workloads will move to areas with spare energy, some energy will be diverted from other industries, and legacy power generation infrastructure like coal and gas plants will be maintained longer than planned.

The company's plan to bridge that gap leans into its business model – repurposing existing energy assets like old thermal power plants, industrial sites, or refineries that bring with them some levels of infrastructure, permits, contracts, and staff.

Such retrofitting has been going on for several years with Bitcoin mining operations – AI tokens can be sold for more than intermittently minted crypto tokens. And the math works for other industries too. 

For example, Teravolt suggests that an aluminum smelter making $170 to $190 of gross revenue per megawatt-hour (assuming 4 to15 MWh per metric ton at an aluminum price of about $2,600) makes more sense as an AI datacenter generating $450 to $900 of revenue and about $300 of EBITDA.

Laert Karaashev, co-founder and managing partner of Teravolt, said he expects almost everything in the AI stack will be commoditized – software, the orchestration layer, chips, and GPUs. 

"But the bottom layer, which is power, it is hard to imagine how to commoditize it," he said.

That is to say, there's no quick way to meet energy demand. It will take years of investment.

The faster way to get there is to cannibalize existing industries, at least while AI workloads are so much more valuable than other industrial output. 

Denis Alkhazov, founder and general manager, argues the margin you can extract from one megawatt of power selling AI compute is two orders of magnitude more than you can get from classic industries like metal production or more recent gambits like cryptocurrency mining.

"The low marginal users of power will be cannibalized by the new form of extracting value from the power," Alkhazov said.

Alkhazov said AI is on the verge of becoming economically self-sustaining and he expects that later this year we'll see companies emerge that build AI services with few people but many AI agents and high token expenditures.

"This process starts from developed countries, where salaries are high," he said, "and it will move to other regions soon."

Karaashev said Teravolt is focused on the market in Eastern and Southern Europe at the moment because there are still good brownfield sites to convert at a reasonable cost. In the US and Western Europe, he said, "those sites are already repriced four or five times more than they cost like five years ago."

The Eastern and Southern European market also makes sense based on timelines demanded by Teravolt's customers.

Alkhazov said most customers – e.g. mid-sized AI labs that want 20,000 GPUs – expect delivery in 12 months or less.

"It's completely unachievable in Western markets," he said. "So you have to be creative and have to shift to other geographies to provide some solutions for that kind of demand." ®