Meta's second-quarter revenue soared 28% to $60.8 billion, but surging AI investments and rising costs sent free cash flow tumbling 91%, rattling investors and raising questions about the payoff from Mark Zuckerberg's AI strategy
Meta Platforms delivered blockbuster sales growth in the second quarter, but Wall Street punished the stock with a sharp selloff after the company's aggressive spending on artificial intelligence slashed profits and nearly wiped out free cash flow. Shares of Meta fell about 9% in early trading Thursday, July 30, as investors reacted to the company's latest financial results and outlook.
Meta, the parent of Facebook and Instagram, reported $60.8 billion in revenue for the quarter, up 28% from a year earlier. Advertising revenue climbed 27% to $59.36 billion, driven by a 14% increase in ad impressions and a 12% rise in average revenue per ad. The company's user base also continued to expand, with 3.6 billion people using at least one Meta app daily in June, a 3% year-over-year increase. Instagram reached 2 billion daily users, and Threads surpassed 500 million monthly users.
Cash Flow Squeeze
Despite the strong top-line performance, Meta's spending on AI infrastructure and research overwhelmed its cash generation. Operating cash flow rose 25% to $31.86 billion, but capital expenditures soared to $31.08 billion, leaving just $784 million in free cash flow-a staggering 91% drop from $8.55 billion a year ago. The company's costs and expenses jumped 55% to $42.03 billion, while operating margin fell to 31% from 43%. Net income declined 14% to $15.85 billion, even as advertising sales surged.
Not all of the margin pressure came from AI. Meta also recorded a $2.4 billion litigation charge and $1.18 billion in severance costs. Still, the scale and pace of AI-related investment dominated the quarter, fueling concerns that Meta is burning through cash faster than it can demonstrate a return on those bets.
AI Ambitions and Investor Skepticism
Meta's leadership has positioned AI as central to the company's future, arguing that advanced AI systems will power new products and open up enterprise opportunities. But the immediate financial impact is clear: Meta is spending at a level more typical of cloud infrastructure giants, without yet generating comparable revenue streams from those investments. Research and development costs jumped to $21.66 billion from $12.94 billion, making it the company's largest operating expense.
Meta also raised the lower end of its 2026 capital expenditure forecast to $130 billion, with a top end of $145 billion, up from previous guidance. The company's full-year expense outlook increased to a range of $165 billion to $169 billion. For the third quarter, Meta projected revenue between $61 billion and $64 billion, with the midpoint falling short of analyst expectations.
For investors, the challenge is clear: Meta must grow its advertising business fast enough to fund a massive infrastructure buildout, defend margins, and convince the market that its AI investments will eventually pay off. The company ended June with $90.26 billion in cash, cash equivalents, and marketable securities, but also carried $83.66 billion in long-term debt. While Meta remains highly liquid, the credibility gap between spending and proven AI returns is widening.
Ad Engine Still Dominates
Meta's advertising machine remains formidable, generating tens of billions in quarterly operating cash flow. The company's ability to attract more advertisers and command higher rates has kept revenue growth robust, even as profitability has come under pressure. Yet the scale of capital spending-$31.08 billion in a single quarter-has few parallels outside the largest technology infrastructure providers.
Some analysts see Meta's current strategy as a calculated risk, sacrificing near-term cash flow to secure the computational power needed for the next wave of AI-driven products and services. Others warn that the company is spending at a pace that could outstrip its ability to deliver new revenue streams, especially if AI monetization takes longer than expected. This tension echoes concerns raised in other parts of the tech sector, such as when investors questioned the sustainability of AI-driven demand at Micron Technology.
According to Meta's filings, the company's capital expenditures are primarily focused on acquiring chips, servers, networking equipment, and data center capacity to support its AI ambitions. The company's guidance suggests that high levels of spending will continue for the foreseeable future, with no immediate relief for margins or free cash flow.
Key Numbers and Outlook
Meta's second-quarter results highlight the trade-offs facing large technology companies as they pursue AI leadership. Free cash flow collapsed 91% to $784 million, capital expenditures hit $31.08 billion, and operating margin dropped 12 percentage points to 31%. Despite a 28% surge in revenue, net income fell 14%. The company's third-quarter revenue guidance failed to reassure investors that the payoff from AI is imminent.
For now, Meta's vast cash reserves and dominant ad business provide a cushion. But the company's ability to convert AI investment into profitable new businesses remains unproven, and the market's patience is being tested by the scale and speed of spending.
Meta's experience underscores a broader challenge for technology giants: balancing the need to invest in transformative technologies with the imperative to deliver near-term financial results. As AI reshapes the competitive landscape, companies that can demonstrate both innovation and financial discipline may be best positioned to win investor confidence.
Free cash flow is a key measure of a company's financial health, representing the cash left after capital expenditures needed to maintain or expand operations. For investors, shrinking free cash flow can signal that a company's investments are not yet generating sufficient returns, or that spending is outpacing revenue growth. In Meta's case, the dramatic drop in free cash flow highlights the risks of large-scale bets on emerging technologies before their commercial potential is fully realized.