Definition
Meta AI is the AI assistant built into Meta's apps (WhatsApp, Instagram, Facebook and Messenger), the standalone Meta AI app and website, and Ray-Ban Meta glasses. It answers questions, generates images, searches the web and shops for users, and since April 2026 it runs on Muse Spark, a proprietary model from Meta Superintelligence Labs.
Distribution is its main advantage. Meta said in May 2025, and again on its October 2025 earnings call, that Meta AI had more than 1 billion monthly users across its apps. It has not published a newer total since, though Mark Zuckerberg told investors in July 2026 that the number of people interacting with Meta AI each day rose 60% after the assistant was rebuilt on Muse Spark. WhatsApp's head Will Cathcart has said India is Meta AI's largest market. Those numbers count people who use the assistant inside apps they already open daily, so they are not directly comparable with standalone chatbot usage.
The model story changed in 2026. Meta built its earlier assistant on the Llama family of open-weight models, but the Llama 4 release in April 2025 disappointed developers, and Meta reorganized its AI work under chief AI officer Alexandr Wang. On April 8, 2026 it launched Muse Spark, code-named Avocado, as the first model in a new Muse series. Unlike Llama, Muse Spark is closed, with only a private API preview for partners and a stated hope to open-source future versions. It added answer modes for quick and complex questions, a Contemplating mode that runs several agents in parallel, and a Shopping mode that draws on creator content and brand posts from Meta's apps. Optimizing for Meta AI is therefore a different question from how Llama-based third-party apps behave.
For search visibility, two things matter. First, Meta AI pulls live web results and cites them. Meta's developer documentation describes a web_search tool for Muse Spark that returns url_citation annotations tying parts of an answer to source URLs. Second, Meta is building its own index. Its crawler documentation describes Meta-WebIndexer as a bot that improves Meta AI search results and helps Meta cite and link to content in Meta AI answers, separate from Meta-ExternalAgent (training) and Meta-ExternalFetcher (user-requested fetches). Promptwatch's crawler logs recorded Meta-WebIndexer rising from about 2% to nearly 38% of tracked AI crawler requests between mid-July and August 9, 2026, as described in our Meta-WebIndexer data study.
The practical steps follow from that. Check robots.txt so Meta-WebIndexer is allowed even if you block Meta-ExternalAgent for training, since a site can refuse training and still be cited. Keep public Facebook and Instagram profiles, product catalogs and business details accurate, because Muse Spark draws on public posts, Reels and Marketplace listings alongside the web. Watch how creators and customers talk about your brand on Meta's platforms, as social signals feed directly into what the assistant surfaces. Then compare Meta AI's answers with ChatGPT, Gemini and Perplexity as part of cross-platform AI visibility tracking, because its source mix leans more heavily on social content than most assistants.
Examples of Meta AI
- A fashion retailer finds that Meta AI's Shopping mode recommends a competitor's jackets using creator Reels, while ChatGPT recommends its own products from review sites. It shifts budget toward creator partnerships on Instagram.
- A publisher's robots.txt blocks every Meta user agent to stop training. After seeing Meta-WebIndexer climb in its logs, it allows that crawler while keeping Meta-ExternalAgent blocked, so its articles can be cited in Meta AI answers.
- A restaurant group in India checks Meta AI inside WhatsApp, where most of its customers ask questions, and corrects outdated opening hours on its Facebook page that the assistant had been repeating.
- A developer building on Llama 3 learns that Meta AI itself now runs on the closed Muse Spark model, so test results from its own Llama deployment say nothing about how Meta's assistant describes its brand.
