Zuckerberg points to Muse as a potential profit engine, but analyst flags heavy losses

Meta Platforms CEO Mark Zuckerberg is betting that Muse, the company’s AI assistant, could become a standout moneymaker within the company’s advertising and engagement businesses. In comments reported by Yahoo Finance, Zuckerberg argued that Muse has the potential to out-earn Facebook and Instagram on a per-user basis, a framing that suggests Meta views the assistant not just as a novelty feature, but as a future monetization layer.

The same report also included a cautionary view from Deepwater Asset Management analyst Gene Munster. Munster said the market should not focus only on Muse’s upside, because Meta appears to be losing money on the product at a pace that exceeds other major launches the company has rolled out in recent years. The comparison is meant to highlight the risk that costs could delay or dilute any eventual revenue impact.

Muse is Meta’s AI assistant product built to help users with tasks and content generation. While Meta has positioned AI broadly across its platforms, the specific claim in the report centers on how Muse might monetize in ways that differ from traditional social feeds. The core question raised by Munster’s assessment is whether Muse can scale efficiently enough to reach profitability without becoming a long-running cost sink.

The Yahoo Finance report does not provide new, detailed financial disclosures about Muse itself, such as product-level revenue, user counts, or cost breakdowns. Without those figures in the article, investors are left to infer the direction of monetization and the magnitude of losses from qualitative comments and broader company spending patterns.

Meta’s broader strategy in AI has been to integrate assistant-style experiences into its ecosystem, where it already has a large, active user base and ad-funded revenue streams. If Muse can drive sustained engagement and measurable conversion, Meta could benefit from additional pathways to advertising, subscriptions, or other forms of commerce. But if usage remains limited or if per-interaction costs remain high, monetization per user may lag behind expectations.

Munster’s warning, as characterized in the report, underscores a common industry tension with consumer AI products. Creating assistant functionality typically requires substantial computing resources, and early phases often involve experimentation, rapid model iteration, and expanding infrastructure. Analysts watching Muse will likely focus on whether Meta can reduce the cost to serve while growing active usage and value to advertisers.

Meta did not, in the reported comments, specify timelines for profitability or quantify how Muse’s economics would compare with Facebook or Instagram at the per-user level. Nor did the report detail what would need to change for Muse to “earn” more per user, such as product packaging, ad integration, pricing, or latency and efficiency improvements.

Next for investors and observers is whether Meta provides more concrete numbers around Muse’s adoption and financial performance, either through product updates, additional management commentary on monetization, or disclosures that help separate AI-assistant economics from the company’s overall spending. Until then, the debate highlighted in the report is likely to remain centered on whether Muse’s potential upside is outpacing the losses required to reach scale.