A MESSAGE FROM BLOOM ENERGY

As AI adoption accelerates, power has become the defining constraint—and opportunity—for data center growth. Our latest 2025 Mid-Year Power Report reveals a dramatic shift in how industry leaders are planning for the future.

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If you happened across a video of a bunch (a gaggle?) of rabbits jumping on a trampoline, you are not alone; the original post on TikTok has been viewed around 230 million times. Too bad nothing about the video is real.

The clip was generated by A.I., something that becomes pretty obvious if you watch closely as one of the bunnies magically (or impossibly) merges with another. Still, the style of video—C.C.T.V.-type footage, nighttime, crickets in the background—is really convincing. Hate to burst your bubble (break your trampoline?).

And now for the main event…

The quest for scale remains a preoccupation at almost every level of the A.I. pipeline: There’s the mind-boggling amount of training data required; the alarming quantity of water and electricity needed to run data centers; and the millions of G.P.U. chips that provide the necessary computing power. Then there are the extraordinary public market valuations for many of the largest A.I. players, which have buoyed the stock market for the past two years.

Just as notable, of course, is the unprecedented capex flooding the industry. In 2023, the four major hyperscalers (Meta, Google, Amazon, and Microsoft) reported a modest $140 billion in total capital expenditures, largely for A.I. chips and data centers. In 2024, that number crossed $220 billion. At the beginning of 2025, that cadre of tech giants forecasted total expenditures of $325 billion for the year. After this most recent round of earnings reports, the total is likely to come in above $360 billion.

And no one really expects this to stop anytime soon. Morgan Stanley analysts Vishwanath Tirupattur and Vishwas Patkar forecast in a recent note that an additional $3 trillion could be invested in data centers globally through 2028. The analysts expect roughly half of that amount to be financed through debt, something that’s already starting to happen—Elon Musk’s xAI has raised more than $5 billion in debt, and is reportedly in talks to raise a further $12 billion; CoreWeave has billions of dollars in debt, something that its C.E.O. has called the “fuel for this company”; Meta is reportedly in talks to raise $26 billion in debt to fund data centers; and OpenAI last year secured a $4 billion line of credit. Historically, a concentration of bank debt tends to make the difference between a crash that everyone walks away from (like in ’02), and a crash that has broader economic impacts (like in ’08).

A MESSAGE FROM BLOOM ENERGY

AI growth is outpacing power infrastructure, making energy strategy a board-level concern. The 2025 Mid-Year Power Report highlights grid delays, rising onsite generation, and the strategic importance of power access.

Get the report.

The scale of investment is so significant, according to Neil Dutta at Renaissance Macro Research, that A.I. capex contributed more to G.D.P. growth than consumer spending did across the first half of 2025. Dr. Paul Kedrosky, a researcher and investor, estimated that A.I. spending alone accounted for nearly half of the 3 percent growth in the U.S.’s latest G.D.P. report. Tejas Dessai, the director of research at Global X, called A.I. the “economy’s new engine” in a recent note.

So far, so good, right? After all, these companies keep exceeding analysts’ expectations as they reinvest their profits into their future. But the role that A.I. plays in their future business units is less transparent than the overwhelming financial narrative. We’re dealing with massive corporations, each of which already has enormous established businesses, making it even more difficult to measure the impact of all their investments in A.I. Deployment of A.I. might lead to, e.g., more (or more valuable) ad sales, or cheaper revenue, or operational efficiencies. But we don’t have a whole lot of visibility into that, and more-direct revenue streams remain decidedly uncertain.

It’s worth putting the scale of these capital expenditures in context. Amazon, for instance, raked in $167.7 billion in revenue for the quarter. Meta handily beat expectations with $47.5 billion in revenue. Microsoft also beat expectations with $76 billion in revenue. Meanwhile, Google earned $96.4 billion in quarterly revenue. Despite their extraordinary investments in A.I., these earnings largely derived from core and well-established business units.

And yet the A.I. narrative, which has contributed some $5 trillion in market cap to the so-called Magnificent Seven since April, buttressed the value of their capital allocation as retail investors plowed hundreds of billions into the stock market, and specifically into tech and A.I. companies. J.P. Morgan expects retail investors to contribute $360 billion, of a total of $500 billion, in equity inflows for the second half of the year. This frenzy of investment just keeps driving valuations higher, pushing the tech weighting of the S&P 500 to around 34 percent, just about double its historical average. Kedrosky told me the valuations are “highly irrational.”

Indeed, corporate investment into A.I. data centers is becoming comparable, as a percentage of G.D.P., to the railroad-building fever of the late 1800s, according to Kedrosky, which culminated in the Panic of 1873. (A.I. capex comprises about 1.3 percent of G.D.P. today; railroads once contributed 6 percent.) The critical difference is that A.I. chips depreciate a lot faster than railroad infrastructure. “A.I. data centers are short-lived, asset-intensive facilities riding declining-cost technology curves, requiring frequent hardware replacement to preserve margins,” Kedrosky warned.

On some level, it seems obvious that we’ve entered an A.I. bubble. Yes, The Four are going to be fine and make more money than ever, but others won’t be as lucky in this Manichean, winners-take-most economy. At the same time, there’s no clear definition for what constitutes an asset bubble, especially when the potential returns are speculative (it’s much easier to call it a bubble after it pops). Winston Dou, a professor of finance at Wharton, articulated the two main schools of thought: One could argue these investments are entirely rational, and the valuations justifiable, if there is a sufficiently high degree of certainty that the bet will pay off. But if expectations fall short of reality, the entire market will have to grapple with valuations coming down across the board. The trouble right now is a total lack of clarity, a blank space that investors have filled with evidence to support their preferred narrative, all centered on upside uncertainty, which seems to have unlimited potential. This is a kind of uncertainty that Dou said “investors want to embrace,” largely because the alternative is gruesome.

As for Meta, Microsoft, Amazon, and Google… well, Dou doesn’t think they have much of a choice. A failure to effectively compete poses significant displacement risks, and when investors keep driving up valuations over excitement around A.I., now certainly seems like a good time to go all-in, even if we’re still waiting to see the flop. But even if it is rational, Dou said that this current environment is just “not sustainable.” At some point, all this uncertainty gets resolved into clear losers and winners, and we’ll see a rapid decline in the market valuation of the entire sector as the losers tank, something that’ll look an awful lot like a crash. This, he said, “is just the nature of the game.”

When the market does correct—or revert to the mean, if you prefer—Kedrosky expects states like California and Virginia, whose economies have benefitted from massive amounts of A.I. spending, to suffer revenue shortfalls, and for funds that are unexpectedly exposed to A.I. to underperform. Mainly, though, he thinks the “price of tokens will collapse, as data centers ‘dump’ supply onto the market, much like OPEC. This will reduce the cost of replacing humans in many occupations, causing accelerated job losses in areas like customer service.” The operative question now is how much patience investors can summon as all this uncertainty plays out.

That’s all for today. I’ll see you Thursday.

Ian

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