Meta Platforms lost roughly 9% of its value in after-hours trading on the evening of May 1, 2026, after the company disclosed a capital spending plan so large it stunned even its most committed backers. In its first-quarter earnings report, Meta said it now expects to spend between $125 billion and $145 billion on infrastructure this year, up from the $39 billion it spent in all of 2024 and far beyond what any other technology company has committed to a single year of building.
Within hours, JPMorgan downgraded the stock to neutral from overweight, stripping away one of Wall Street’s most prominent bullish endorsements at the worst possible moment.
The sell-off was not triggered by a bad quarter. It was triggered by the cost of what comes next.
A strong quarter overshadowed by a massive spending plan
Meta’s first-quarter results were, by conventional measures, excellent. Revenue topped Wall Street expectations, driven by a 19% year-over-year increase in ad impressions and a 12% rise in the average price per ad, according to the company’s quarterly filing with the SEC. Both metrics point to sustained strength in Meta’s advertising engine across Facebook, Instagram, Threads, and its broader app ecosystem.
Net income received an additional lift from a one-time tax benefit the company attributed to a recent change in federal tax guidance. That windfall boosted the bottom line for the quarter but is not expected to repeat, making it a misleading gauge of ongoing profitability.
None of it was enough to offset the capex shock. At the midpoint of the new range, Meta would spend roughly $135 billion this year on data centers, custom chips, networking gear, and other infrastructure needed to train and deploy increasingly powerful AI systems. For context, Alphabet has guided to approximately $75 billion and Microsoft has signaled around $80 billion in 2026 capital expenditures, according to figures each company disclosed in its most recent quarterly earnings report. Meta’s upper-end figure nearly doubles either commitment.
What all that money is actually building
CEO Mark Zuckerberg laid out the rationale on the company’s earnings call, framing AI as the single most important investment Meta will make this decade. The spending spans several overlapping efforts: scaling the Llama family of open-source AI models, embedding AI assistants into WhatsApp, Messenger, and Instagram, and rebuilding Meta’s ad-targeting and content-recommendation systems on machine learning architectures that demand enormous computing power.
But the sheer scale of the commitment raises questions the company has not fully answered. Meta’s quarterly filing does not break down how the capex budget is allocated across specific projects. Investors cannot see how much is earmarked for generative AI model training versus new data center construction versus the ongoing augmented and virtual reality hardware work inside Reality Labs.
That lack of granularity is a problem. Without it, shareholders are being asked to trust that management is deploying capital efficiently across a sprawling set of bets, some of which have no clear timeline to profitability.
Why JPMorgan walked away
JPMorgan’s downgrade carried outsized significance because the firm had been one of Meta’s most vocal supporters during the stock’s dramatic recovery from its 2022 lows. The shift to neutral represented a notable reversal in sentiment at a moment when the stock was already under pressure from the capex disclosure.
The core concern is straightforward: capital intensity is rising faster than revenue, a dynamic that compresses margins and makes the stock harder to justify at its current multiple. When a company spending $145 billion a year needs to show proportional returns, the margin for error shrinks considerably.
Not every analyst agreed with the call. Several firms maintained their buy ratings in the hours after the report, arguing that Meta’s advertising business generates enough cash flow to absorb the spending without jeopardizing the balance sheet. The split in opinion reflects genuine uncertainty: whether this level of investment is visionary or reckless depends almost entirely on assumptions about AI monetization that no one can yet prove.
It is also worth noting that the 9% after-hours decline occurred in a low-volume trading session, where price swings tend to be amplified. The stock’s performance in the following regular session would offer a more reliable read on institutional sentiment.
The math Meta is asking shareholders to accept
What makes this moment so striking is the gap between Meta’s present and the future it is building toward. The advertising business is healthy by nearly every measure. Impressions are growing, pricing power is intact, and the company’s recent cash flow generation has been strong enough to fund massive infrastructure buildouts without taking on unsustainable debt.
But $145 billion is not a cautious hedge. It is a bet that AI infrastructure will prove as foundational to Meta’s next era as the mobile pivot was to its last one. The difference is that the mobile transition had a visible payoff almost immediately: smartphones put Facebook and Instagram in billions of pockets. The AI transition, by contrast, requires years of spending before the revenue impact becomes clear.
Meta’s filings confirm the scale of the wager. What they cannot yet show is whether the AI products and capabilities built on top of all that infrastructure will generate returns large enough to justify it. Until that evidence arrives, the stock will trade on faith as much as fundamentals, and after May 1, 2026, that faith got considerably more expensive.
David M. Keller is a finance writer based in Columbus, Ohio, covering personal finance and consumer-focused economic topics. He earned his degree in journalism from Ohio University and began his career reporting on local business and economic trends for a regional media outlet. Since then, he has contributed to a variety of online publications, focusing on clear, practical coverage of topics such as cost of living, debt, and everyday financial decision-making.
