Meta targets enterprise revenue from AI agents, APIs, software tools and compute

Meta outlined a broader enterprise AI strategy during its second-quarter earnings call on Wednesday. After launching a business agent in June, the company is now considering APIs, productivity tools, business agents and direct compute sales.

Why Meta is looking beyond advertising

Advertising still generates most of Meta’s revenue, while subscriptions account for a smaller share. AI services could create additional income by extending relationships with millions of advertisers and hundreds of millions of small businesses already using its platforms.

The initial model resembles performance advertising: agents will interact with customers through messaging services, and Meta expects to be paid when those systems deliver results. However, Mark Zuckerberg acknowledged that enterprise sales require a “different muscle” from Meta’s traditional business.

Agents, internal tools and compute

Meta is also building coding, development and internal productivity systems tuned to its own operations. Zuckerberg said these tools could eventually be offered to both small companies and larger enterprise customers.

“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.”

Compute is another possible revenue stream. Meta said capacity could currently be sold at a significant premium to its cost, but Zuckerberg warned that selling all of it for short-term profit would be foolish. That balance reinforces the prospect of monetising surplus AI capacity, because Meta still needs infrastructure for superintelligence and future hardware.

The strategy extends beyond corporate buyers. Meta is developing personal AI agents and smart glasses, while large language models are accelerating experiments for Marketplace sellers, Facebook Groups and vibe-coded games. Zuckerberg expects AI to make launching and scaling new apps easier.

For businesses, the practical implication is to compare AI suppliers on measurable outcomes, integration depth, support and guaranteed capacity. Meta brings exceptional distribution, but customers should test whether its emerging enterprise operation can match the reliability of established vendors.