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Is it just a Ponzi scheme? That is the question that currently haunts American tech — and wider markets — as the valuation of artificial intelligence-linked groups soars to evermore eye-popping heights.
Indeed, calculations by the FT suggests that ten lossmaking AI start-ups — such as OpenAI, Anthropic and Elon Musk’s xAI — now command a collective valuation of close to $1tn, while venture capital has poured $161bn into AI overall this year.
More startling still, few of these entities expect to turn a profit anytime soon — and these valuations are being boosted by variants of cross-cutting vendor financing, like recent deals between OpenAI, Nvidia, Oracle, AMD and Broadcom.
The net result is a pattern of circular flows that echo some of the hairball of interconnections that emerged between banks and insurance companies via credit derivatives before 2008. And those, remember, resulted in unseen concentrations of risk — and subsequent contagion when the bubble burst.
Hence why institutions such as the IMF are now warning of bubble risks comparable to the 1999 dotcom mania. And why even tech luminaries, like Jeff Bezos, admit there is excessive exuberance — although he also insists that since this is “a kind of an industrial bubble as opposed to financial bubbles” it will be “good” for the world by installing the digital infrastructure needed for future innovation.
Maybe so. However, there is another way to frame events. Most notably, a century ago, anthropologists noticed that some Melanesian islands had created so-called “cargo cults” — a 19th century phenomena that emerged when westerners arrived and flooded the islands with previously-unseen consumer goods.
For locals, this seemed utterly baffling, particularly when “metal birds” (aka planes) arrived during the second world war. So they later tried to unleash this seemingly magical deluge by replicating the intruders’ symbols, say by hoisting US flags or building bamboo effigies of planes. In short: a copycat cult emerged that confused correlation and causation.
Decades later, physicist Richard Feynman borrowed this metaphor to decry “cargo cult science”, cases where researchers “follow all the apparent precepts and forms of scientific investigation, but they’re missing something essential, because the planes don’t land”.
The same analogy now applies to AI. Almost every business executive today is eager to tell investors about their AI strategy (even though 95 per cent of companies have not (yet) seen revenue gains) and every VC group is keen to show AI plays.
Similarly every Big Tech executive is investing in massive data centres, even though Bain reckons some $2tn of revenue will be needed to fund this by 2030. And charismatic figures like Sam Altman, CEO of OpenAI, keep promising fresh magic. Or as Stephan Eberle, a software engineer, laments: “Watching the industry’s behaviour around AI, I can’t shake this feeling that we’re all building bamboo aeroplanes [like cargo cults] and expecting them to fly.”
Don’t get me wrong: I am not denying the extraordinary potential of AI to change aspects of our world, nor that savvy entrepreneurs, companies and investors will win very big. It will — and they will.
Nor would I discount the idea that this mania might, as Bezos suggests, eventually deliver societal benefits. We are probably living through a replay of the 19th century railway mania, which crushed many investors when the bubble burst — but did at least install the track network that benefited later generations.
Indeed, it is possible that the only way American capitalism can ever amass the scale of investment needed to create this type of ambitious infrastructure is via such manias. That, at least, is the argument I have heard from some White House officials — and techies — who see this as the best route to compete with Chinese state capitalism. (Although, as Bill Janeway, an economist and former VC investor, points out, this will be futile if the Trump administration undermines the “golden goose” of science).
“[This is] a systemic, strategically mediated form of intra-industry risk-splitting,” says Francisco Sercovich, of the University of Buenos Aires, who sees this as an extreme version of how “the Sematech consortium of the late 1980s and early 1990s pooled corporate and federal capital to stabilise US semiconductor R&D against Japanese dominance”.
But even if this “risk-splitting” model does eventually justify itself. we cannot forget the “cargo cult” problem — or the casualties that will arise when the bubble bursts and magical thinking ends.
What might spark that? There are many possible causes: rising interest rates; supply chain disasters; an energy crunch; new innovations, like neurosymbolic AI, that leapfrogs the “transformers” (probability-based) AI systems or just cheaper versions of existing AI, like that from DeepSeek.
Either way, anyone engaged in this AI frenzy needs to watch out for that hairball of interconnections, hedge their bets — and read up on those Melanesian cargo cults.
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