Donald Trump\u2019s most immediate concern in demanding Iran reopen the strait of Hormuz may be rocketing US gasoline prices, but if the conflict drags on, higher energy costs will be felt far beyond the pumps.<\/p>\n
Systemically higher power prices and fractured supply chains will squeeze industries and consumers worldwide. For the US, one consequence may be to threaten the fragile economics of the AI boom.<\/p>\n
Many oil-importing economies, especially in the global south, are having to contemplate outright shortages of oil and its products. Shops in Egypt face curfews, Indonesia has imposed work from home Fridays and the Philippines has declared a national energy emergency.<\/p>\n
As a wealthy oil exporter, the US can largely dodge these concerns. However, as the rising cost of filling up US cars illustrates, it cannot completely avoid the global rise in energy costs \u2013 which many analysts now believe will persist for months even if the strait reopens within days.<\/p>\n
As a result, many companies will be looking anxiously at their cashflow projections. But for a uniquely energy-hungry industry, whose business model is not yet firmly established and whose investments are financed by huge debts, the challenges may be particularly acute.<\/p>\n
OpenAI\u2019s Sam Altman made a less than reassuring <\/a>comparison in February as he sought to play down fears about AI\u2019s environmental impact in the run-up to what is expected to be a mega launch on to the stock market later this year.<\/p>\n \u201cPeople talk about how much energy it takes to train an AI model \u2013 but it also takes a lot of energy to train a human,\u201d he said. \u201cIt takes about 20 years of life \u2013 and all the food you consume during that time \u2013 before you become smart.\u201d<\/p>\n The Bank of England highlighted the potential link between energy costs and the share prices of AI companies in its regular survey<\/a> of the risks facing the UK financial system last week.<\/p>\n The Bank\u2019s financial policy committee began by pointing out that investors had already been raising questions about the sector before Trump went to war. \u201cPrior to the conflict, increasing debt-financing needs and concerns about whether expected returns on very significant AI-related investments would materialise led to selling pressure,\u201d it said.<\/p>\n \u201cThe conflict could increase these concerns, particularly given the energy-intensive nature of the supply chain for key components and the operation of datacentres.\u201d<\/p>\n The Bank of England has highlighted the potential link between energy costs and the share prices of AI companies. Photograph: Dan Kitwood\/Getty Images<\/p>\n It was one aspect of a wider warning that the Iran war could exacerbate pre-existing fragilities in markets, given the likelihood that it will \u201cweigh on growth, increase inflation and tighten financial conditions\u201d.<\/p>\n The chief economist of the World Trade Organization, Robert Staiger, has also made the connection between AI and the impact of the conflict, telling me last month <\/a>that a prolonged period of high energy prices could \u201ccrimp\u201d investment in the sector. \u201cThe boom is very energy intensive,\u201d he said.<\/p>\n To underline the real-world consequences of a possible retrenchment, in its latest global trade outlook<\/a>, the WTO calculated that 70% of investment growth in the US in the first three-quarters of last year was in AI-related goods of one kind or another.<\/p>\n The sheer complexity of the financial engineering underpinning the AI investment mega-boom was laid bare<\/a> in a forensic <\/a>note by a US law firm, Quinn Emanuel, published last month, which kicked off by noting that the sector\u2019s revenues last year were about $60bn (\u00a345.3bn) and its capital expenditure $400bn.<\/p>\n For those of us old enough to remember the 2008 global financial crisis, it makes sobering reading \u2013 off-balance sheet special purpose vehicles feature heavily, as do asset-backed securities.<\/p>\n Essentially, the \u201chyperscalers\u201d leading the AI charge, and infrastructure providers such as CoreWeave, are borrowing unimaginably large sums as they dash to build out datacentres (although recent analysis by the AI sceptic Ed Zitron<\/a> suggests real-world projects lag far behind the promises).<\/p>\n The lenders are often private companies such as asset managers, which makes each company\u2019s total liabilities harder for regulators \u2013 or even their investors \u2013 to track.<\/p>\n