In June, Meta introduced an AI agent targeted at businesses to assist with customer service, support and other daily operations. On the company’s second-quarter earnings call, CEO Mark Zuckerberg told investors that Meta’s ambitions in enterprise AI extend well beyond that single product.
“We see a large enterprise opportunity to sell to businesses, including APIs, business agents, potentially selling compute directly, and other services that we’re building for large customers,” Zuckerberg said. Such additions could create revenue streams beyond advertising, which currently accounts for the bulk of Meta’s income, and subscriptions, which represent a smaller portion.
Initial focus: serving existing advertisers and small businesses
Meta plans to first leverage its existing base of advertisers by offering AI agents that operate across messaging apps and other channels, enabling businesses to interact with their customers through AI interfaces. “And, just like the ad system, effectively, we will get paid when we deliver results for those businesses,” Zuckerberg said. “We view this as an extension of the sales and the partnerships that we have with many millions of advertisers and hundreds of millions of small businesses that use our platforms.”
Expanding to larger enterprise customers and selling internal tools
Zuckerberg described plans to expand beyond small-business advertisers by making Meta’s internal coding and productivity tools available to external customers in the future. “There are other enterprise customers who I think we’re increasingly going to serve, too,” he said. “We’re building coding and developing and internal productivity tools partially because we need to build them ourselves, and we need to make sure that we have tools that are tuned for ourselves. Now that we have those, we feel like there’s a large opportunity to serve — whether that’s small businesses or larger businesses.”
He acknowledged that selling to enterprise customers is a different capability than Meta has historically exercised, and thus may be challenging.
Selling compute and a portfolio approach to infrastructure
On the topic of selling compute to enterprise customers, Meta emphasized a balance between generating revenue and preserving capacity for its own long-term plans. The company noted multiple times that it currently has an opportunity to sell compute at “a significant premium over what we paid for it.”
However, Zuckerberg warned that it “would be foolish” to “sell all of the compute and take a short-term profit.” He described Meta’s strategy as a “portfolio” that mixes short-term sales with long-term retention of infrastructure for future needs. “As we get closer to personal superintelligence, we are . . . going to need hardware that allows you to seamlessly interact with it,” he said.
Agentic AI and consumer-facing products
The call also highlighted Meta’s ambitions for agentic AI — systems that can act on behalf of people or businesses, rather than simply answering questions. These capabilities will be offered not only to enterprise clients but to consumers as well. Meta is promising “personal AI agents” for users and AI-enabled smart glasses that can interact with the surrounding world.
Using LLMs to speed social app development
Meta is also using large language models to accelerate the rollout of new social applications. Recent launches and experiments include:
- an app for Marketplace sellers,
- an app for Facebook Groups,
- apps for vibe‑coded games,
- and other experiments.
Zuckerberg suggested more such products are coming: “I expect it to become a lot easier to ship new apps. So we are planning to build out more ideas and use our recommendation systems to scale them to the people who will find them interesting.”
Practical implications
In practical terms, Meta’s strategy focuses in the near term on expanding AI services for its current advertisers and small businesses, in the medium term on selling internal tools and compute to external customers, and in the long term on maintaining infrastructure capacity for future, more demanding AI uses. Observers will be watching for new product releases, the development of enterprise sales channels, and how Meta manages the trade-offs involved in selling compute while reserving enough capacity for its future AI ambitions.
