Meta Platforms, Inc. reported second-quarter 2026 revenue of $60.80 billion, a 28% year-over-year increase, while earnings per share of $6.18 missed analyst estimates. During the earnings call, executives positioned artificial intelligence as the central engine of the company's next growth phase, detailing AI-driven improvements across advertising, content recommendations, and new enterprise products-alongside a sharp rise in infrastructure spending.
AI Boosts Core Advertising and Engagement
Mark Zuckerberg, founder, chairman and CEO, said AI investments are already strengthening Meta's core operations. "AI investments are already improving Meta's core operations by enhancing user experiences, advertiser performance and internal product development," he said, pointing to better recommendations on Instagram and Facebook. Susan Li, chief financial officer, added that global time spent on Instagram grew double digits year over year, supported largely by improvements in feed and Reels recommendations. Facebook video watch time also rose, driven by ranking gains.
New Revenue Channels Beyond Advertising
Meta is building multiple AI-related revenue streams, including subscriptions, APIs, business agents, and potential compute services. Zuckerberg said the company sees enterprise opportunities beyond advertising, with tools that help businesses interact with customers and improve operations. More than 1 million businesses were using Meta business agents each week across WhatsApp and Messenger, and the company is expanding those capabilities to Instagram. Li noted that Family of Apps other revenues reached $1 billion for the first time in a quarter, growing 73% year over year, primarily from WhatsApp paid messaging and subscriptions.
Infrastructure Spending Hits $31 Billion in the Quarter
Capital expenditures totaled $31.08 billion in Q2, reflecting heavy investment in servers, data centers, and network infrastructure. Li said Meta expects full-year 2026 capital expenditures, including principal payments on finance leases, to remain between $130 billion and $145 billion. The company is focused on maximizing capacity through 2026 and 2027 while maintaining flexibility. Management also discussed external funding partnerships, such as the BlackRock infrastructure venture, to complement its approach to expanding AI capacity.
Costs Rise as AI Investments Grow
Total expenses jumped 55% year over year to $42.03 billion, driven by employee compensation, infrastructure costs, legal expenses, and third-party AI token costs. Operating income fell 8% to $18.8 billion, producing a 31% operating margin. Excluding legal charges and severance, Li said operating income would have increased 9%. The company raised the lower end of its full-year expense outlook to $165 billion to $169 billion, incorporating legal charges, and forecast Q3 revenue between $61 billion and $64 billion.
Analysts Probe Returns on AI Spending
In response to a Morgan Stanley analyst's question about which AI opportunities could scale first and generate measurable returns, Zuckerberg said Meta sees potential across core business improvements, consumer products, APIs, business agents, and compute monetization rather than relying on a single opportunity. A Goldman Sachs analyst asked about enterprise opportunities and capital needs; Zuckerberg described business agents as an extension of Meta's existing advertiser relationships, while Li emphasized a mix of operating cash flow, debt, and partnerships to fund infrastructure. A JPMorgan analyst inquired about recommendation gains from larger AI models-Li said the company expects continued improvement through more personalized recommendations and expanded use of large language models in ranking systems.
Why this matters for executives and strategy
Meta's earnings call underscores how a dominant consumer platform is betting heavily on AI infrastructure as a multi-year growth lever, even as near-term margins compress. For strategy leaders, the key takeaway is the deliberate layering of monetization paths-advertising improvements, business messaging, API access, and potential compute services-rather than a single breakthrough product. The scale of capital commitment, paired with flexible funding partnerships, signals that Meta intends to make AI capacity a durable competitive advantage while managing regulatory and cost risks. Executives tracking how companies operationalize AI at scale can find broader analysis through Complete AI Training's AI for Executives & Strategy resources.
Your membership also unlocks:
