The AI Boom Is Setting Itself Up for a Crash
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The global rush to build AI infrastructure is arguably the biggest economic narrative of our time. Yet when you look closely at the math behind it, the story becomes far less convincing.
To some, artificial intelligence is destined to become the defining technology of this century. To others, it is a classic bubble inflated by hype. The truth sits somewhere in between. Much like the railroad frenzy of the 1800s or the broadband explosion of the late 1900s, AI will likely surge, stumble, and only afterward settle into a world-changing role.
The Spending Problem: A New Apollo Program Every Ten Months
Right now, the financials look out of proportion. Tech giants are expected to pour nearly $400 billion this year alone into the hardware and infrastructure needed to train and run AI systems. In sheer spending, no group of companies has ever attempted something of this magnitude.
For comparison, the Apollo program’s budget—adjusted for today’s dollars—was about $300 billion to send astronauts to the moon over an entire decade. Today’s AI race is effectively demanding a new Apollo-level investment every ten months.
Costs That Can’t Be Recovered
What’s even more troubling is that many firms don’t seem positioned to recover those costs — but intend to keep spending anyway. AI capital expenditures in the U.S. are on track to surpass $500 billion in both 2026 and 2027, roughly equivalent to Singapore’s annual GDP.
Meanwhile, consumer spending on AI services in the U.S. barely hits $12 billion a year, comparable to the GDP of Somalia. If you can picture the economic divide between those two countries, you can picture the gulf between AI’s lofty promises and its current market reality.
Some reports even show that enterprise use of AI tools is slipping, as many large organizations still struggle to figure out how these models actually reduce costs or improve efficiency.
Red Flags: The Classic Signs of a Bubble
Every financial bubble contains moments that, in hindsight, make you wonder how anyone paying attention could have missed the warnings. Today, those warning lights are flashing everywhere.
Thinking Machines—a fledgling AI company led by former OpenAI executive Mira Murati—just secured the largest seed round ever: a staggering $2 billion at a $10 billion valuation. The catch? The company hasn’t released a single product and won’t even tell investors what it plans to build. One investor described the pitch meeting as surreal: “It was the most ridiculous conversation. She basically said, ‘We’re starting an AI company with top-tier talent, but we can’t tell you anything about it.’”
Stock Market Logic Has Broken Down
Fresh analyses of the stock market reveal that the usual logic behind long-term investing has fractured. Traditionally, stock prices move in line with earnings and business fundamentals. But today’s market is propelled mostly by momentum, as retail traders rush into meme stocks and AI-themed equities simply because they believe everyone else is doing the same.
Creative Accounting: A Dangerous New Phase
Bubbles also tend to feature signs of financial engineering gone off the rails — just think of the complex debt instruments and subprime mortgage bundles that detonated during the mid-2000s housing crash.
Worryingly, AI seems to be sliding into its own era of creative accounting. As The Economist notes, major AI hyperscalers — the companies spending the most on infrastructure — are using accounting maneuvers to make their capital outlays look smaller on paper. The result: profits appear larger than they truly are.
