Meta pushes into business AI with new agent for companies

Meta pushed deeper into commercial artificial intelligence on Wednesday, unveiling Meta Business Agent as a tool for companies that rely on WhatsApp, Messenger and Instagram to reach customers. The product expands Meta’s existing business messaging services into what the company calls agentic capabilities, with software that can answer questions, recommend products, book appointments, qualify leads and close sales, while still letting a human step in when needed. More than 1 million businesses already use earlier chatbot versions on WhatsApp and Messenger.

The company is betting that scale, not novelty, will be its edge. Meta says a billion people already connect with businesses across WhatsApp, Messenger and Instagram every day, and it is opening the new agent globally for companies of all sizes. The agent can be set up in minutes, plugged into existing enterprise systems, and will start as a free product before moving to paid subscriptions in the coming months. Meta is also expanding the tool to Instagram and testing broader functions such as morning briefings, market research, product insights, calendar management and competitive intelligence.

That makes the launch more than a product update. It is a bid to turn Meta’s spending on AI models, infrastructure and integration into a revenue stream beyond advertising, which still supplies the bulk of the company’s money. The logic is straightforward: if Meta can make its messaging apps more useful for merchants, support teams and advertisers, it can sell AI where it already has distribution, rather than trying to build demand from scratch.

But Meta is entering a workplace AI market that is already crowded. Microsoft sells Microsoft 365 Copilot Business as an AI tool for work, with secure chat, search and agents built into its business suite, while Google offers Gemini Business and Gemini Enterprise for Workspace customers. Meta’s main advantage is reach, not a uniquely new AI concept. The harder test is whether businesses trust its agent with customer data, whether the system stays accurate under pressure, and whether it saves enough time or drives enough sales to justify adoption.