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🔥BTC/USDT

Meta awaits Q3 results as AI costs rise

2026-10-21 08:28

Meta Platforms’ third-quarter report will put less emphasis on whether the company clears near-term advertising forecasts than on whether its artificial intelligence spending is moving toward a credible payoff. Bank of America expects revenue of $63.8 billion for the quarter, slightly above the $63.3 billion consensus cited in the bank’s preview, but sees 2027 spending plans and AI monetization timelines as the issues most likely to shape the market response.

Justin Post, an analyst at Bank of America, said his revenue forecast reflects advertising channel checks that indicate continued growth in Meta’s core ads business. Advertising remains the financial engine funding the company’s push into AI infrastructure, including the data centers, chips and computing capacity required to train and run increasingly complex models.

The report is due after the market closes on Oct. 21. Meta’s results could be distorted by a one-time $10 billion accrual related to a settlement with state attorneys general, according to Post’s forecast. The charge would reduce reported, or GAAP, operating profit to $11.5 billion, well below the $18.6 billion market estimate included in Bank of America’s note.

That accounting effect would also bring reported earnings per share to $3.79, versus the $6.08 consensus estimate cited by Post. Excluding the one-time item, Meta’s underlying profitability would be stronger than the headline figures suggest, making management’s explanation of the charge and its treatment central to the earnings call.

Spending outlook could outweigh the quarterly beat

Meta’s capital spending is becoming a larger valuation question as the company races to expand its AI capabilities. Post’s framework for the report focuses on whether management raises its expectations for 2027 capital expenditures or operating expenses, and whether the company gives any indication that meaningful AI revenue will arrive later than previously expected.

Those two questions are closely linked. Building AI products requires substantial upfront investment in specialized computing equipment and power-intensive data centers. Costs arrive immediately, while revenue can take longer to develop through advertising tools, business software, consumer products or other services.

Bank of America’s updated models project a 2027 budget of $205 billion. The estimate underscores how much cash large technology companies may be willing to commit before AI products prove they can produce returns commensurate with the infrastructure buildout.

Meta has already positioned AI as a way to improve advertising performance, recommendation systems and user engagement across its platforms. Those applications can be easier to connect to existing revenue than entirely new standalone products. Yet Bank of America’s note points to products such as Muse, which require significant computing resources without direct revenue at present, as a potential pressure point in evaluating the pace of returns.

A higher spending forecast would not automatically signal a weaker business. Meta has historically used its advertising cash flow to finance long-term technology bets. The more difficult issue for traders is whether the company can show that its AI-related costs are producing commercial benefits quickly enough to justify another step up in infrastructure investment.

AI revenue assumptions face a 2027 test

Savita Subramanian, equity strategist at Bank of America, said capital expenditure growth across large technology companies has been running near 50%, compared with revenue growth of about 20%. The difference leaves a substantial gap between current outlays and the revenue growth needed to support them.

Bank of America’s models assume AI-related revenue starts catching up with capital spending in the second half of 2027. Meta’s commentary could affect that assumption even without a formal revision to financial guidance. Signs that AI products are gaining commercial traction would support the view that the spending cycle is building future earnings capacity. A longer development timetable could force analysts to reassess margins, free cash flow and valuation expectations.

The issue is especially relevant for Meta because its advertising operation has remained resilient enough to fund investment at scale. Strong quarterly revenue would demonstrate that demand for its ad inventory remains intact. It would not settle the longer-running debate over whether the company’s AI expenses are expanding faster than the revenue opportunities they are meant to create.

Management may also face questions about the balance between capital expenditures and operating costs. Capital expenditures generally cover long-lived assets such as servers and data-center equipment, while operating expenses include recurring costs such as staff, research and day-to-day infrastructure operations. Both can rise as AI models become more demanding, but they affect profit and cash-flow measures differently.

Options market prices a smaller-than-usual move

Bank of America’s derivatives data showed options implying a roughly 4.1% move in Meta shares around the results. That is below the stock’s average realized earnings-day move of 7.4% across the previous eight quarters, according to the bank.

The bank also placed Meta’s implied-volatility score near the bottom of its long-short screens, indicating that options protection was relatively inexpensive compared with the stock’s recent earnings volatility. The setup suggests that the options market is pricing a more contained reaction than Meta has often delivered after quarterly reports.

A revenue beat alone may therefore be insufficient to determine the stock’s direction. The market’s focus is likely to shift quickly from third-quarter advertising demand to the size of Meta’s next infrastructure commitment, the treatment of the legal accrual, and the company’s evidence that AI tools are becoming a measurable source of future revenue rather than an expanding cost base.


Want deeper context on AI-driven markets? Explore AI market shifts and connect Meta’s spending to broader tech volatility.

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