AI data center building boom risks fueling future debt bust, bank warns

Soaring optimism about AI has set off a huge global boom in data center construction that could be storing up problems for the future if the sector suffers a sudden correction.

That’s the thinly-disguised message from two interventions by the Bank of England (BoE) last week. The first was an analysis, published on Friday, that examines how AI is creating deeper financial dependencies across the tech sector and beyond.

At the heart of this are data centers, the element on which the whole AI economy depends. AI needs a lot of them, which will cost $5.2 trillion worldwide by 2030 to build, according to McKinsey. The BoE suspects that meeting this demand will increasingly involve companies taking on extra debt, which is where its anxiety starts to rise.

The sums of money estimated to be going into the data center sector are huge, dwarfing previous tech booms over similar timescales. Should the AI market hit problems — for example, after a dot.com-like market correction — the banks making those loans could face losses on a scale that risks wider economic problems, said the BoE.

In case the message was missed, BoE sources separately told Bloomberg that the BoE is currently reviewing the scale of lending to the data center sector and the interconnections between its leading companies.

Economics are good when demand remains high

From the bank’s perspective, building huge AI datacenters isn’t that different to property development. The economics are good as long as demand remains high. If demand drops, an AI data center that can’t easily be put to alternative use turns into another large building nobody wants.

However, that’s only one part of the problem. Meeting the power demands of AI data centers will require the energy sector to make large investments. Then there’s data center demand for microprocessors, rare earth elements, and other valuable metals such as copper, which could, in a bust, make data centers the most expensively-assembled unwanted assets in history.

“Financial stability consequences of an AI-related asset price fall could arise through multiple channels. If forecasted debt-financed AI infrastructure growth materializes, the potential financial stability consequences of such an event are likely to grow,” warned the BoE blog post.

“For companies who depend on the continued demand for massive computational capacity to train and run inference on AI models, an algorithmic breakthrough or other event which challenges that paradigm could cause a significant re-evaluation of asset prices,” it continued.

According to Matt Hasan, CEO of AI consultancy aiRESULTS, the underlying problem is the speed with which AI has emerged. “What we’re witnessing isn’t just an incremental expansion, it’s a rush to construct power-hungry, mega-scale data centers,” he told Network World.

Could be worse than the dot.com bust

The dot.com reversal might be the wrong comparison; it dented the NASDAQ and hurt tech investment, but the damage to organizations investing in e-commerce was relatively limited. AI, by contrast, might have wider effects for large enterprises because so many have pinned their business prospects on its potential.

“Your reliance on these large providers means you are indirectly exposed to the stability of their debt. If a correction occurs, the fallout can impact the services you rely on,” said Hasan.

Meanwhile, some now believe that AI data center investment is draining money from other things, including US President Trump’s attempts to persuade companies to build more factories in the US. Sceptics have also warned about the folly of pushing money through startups like OpenAI, and of the likelihood of a painful market reversal.

Perhaps, it has also been suggested, bubbles are a necessary phase in every technological wave, a list of which, in addition to the dot.com implosion, would include excessive investment in internet and telecom infrastructure around the same time.

A more gradual slowdown is also possible. In this scenario, limitations in adjacent technologies such as storage slow the growth of AI, not the lack of AI data center capacity as such.  Either way, at some point, experts say, the AI and data center market will need to consolidate into fewer more stable companies to prevent the dire consequences of the ballooning debt.

This article originally appeared on Network World.