Key takeaways AI-exposed companies are heavily investing in CapEx to build the infrastructure capable of sustaining current and future AI demand
Bears see similarities with the dot-com bubble: too many startups, stretched valuations, and execution risk
Bulls argue that AI is more about infrastructure, rather than software, with long-term pricing power and stickier usage
The question is not whether AI will survive in the long run, but what the magnitude of its impact will be, based on how effectively demand, infrastructure, and returns align
The equity market has rarely been this confident and divided. Major indices continue to hit record highs, mostly driven by a small group of AI-exposed megacaps.
Capital is pouring into artificial intelligence at a historic pace, valuations are expanding ahead of cash flows, and infrastructure spending is reaching levels previously reserved for national-scale projects.
To some, this looks like the early innings of a productivity revolution. To others, it has all the hallmarks of a classic bubble.
Even experts have polarized views. On one end of the spectrum, skeptics like Gary Marcus warn that expectations have raced far ahead of the technology’s actual capabilities, while valuation-focused voices such as Aswath Damodaran caution that parts of the current AI boom look a lot like the dot-com bubble.
On the other end, market strategists like Josh Brown and Tom Lee argue that investors are still underestimating the scale of the opportunity, comparing AI to past platform shifts whose true economic impact only became clear years later.
Who’s right?
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