Goldman Sachs Group, Inc. Interprets Meta (META.US) AI Paradigm Shift: MuseAI Ushers in a New Era of Intelligent Agents

Recently, Meta (META.US) launched its personal AI agent product Muse AI, marking consumer artificial intelligence's formal leap from Q&A-style chat Siasun Robot&Automation to an era of intelligent agents capable of autonomously completing real-world tasks. Goldman Sachs Group, Inc. released a research report maintaining a "Buy" rating on Meta, with a 12-month target price of $725, implying 11.9% upside from the stock price of $648.03 at the time of the report, while analyzing the product's potential, competitive moats, profitability prospects, and potential risks. "From Conversation to Action": Muse AI Reshapes the C-End AI Product Form Muse AI differs from traditional conversational Siasun Robot&Automation. Leveraging the Muse Spark1.3 model, it can autonomously browse web pages, fill out forms, and complete purchases, realizing a new "conversation-to-action" paradigm and covering high-value personal workflows such as travel booking, bill negotiation, and administrative affairs. The product connects multiple entry points across App, web, and WhatsApp, retaining a messaging interaction logic to lower the user onboarding threshold. On the commercialization front, Meta has for the first time introduced a tiered C-end AI subscription model, offering three tiers: free, a $20/month Power version, and a $100/month Supreme version, with usage permissions divided by Token quotas. Over the long term, it is expected to expand monetization channels such as agent e-commerce transaction revenue sharing and advertising. On the security front, the product uses isolated virtual machines to run tasks, paired with the Sentinel permission control system, retains WhatsApp encryption technology, and keeps data isolated from the advertising system. However, consumer privacy concerns remain the core obstacle constraining large-scale adoption of the product. Ecosystem Distribution Builds a Moat, Industry Landscape Set for Platform-Based Concentration Meta's greatest advantage comes from the distribution barrier created by its social ecosystem. Relying on the billions of active users across Facebook, Instagram, and WhatsApp, and integrating a full infrastructure of accounts, payments, and advertising, it forms a competitive advantage that independent AI startups find difficult to catch up with. The research report judges that at this stage Meta will prioritize expanding user scale and will not rush to pursue commercialization revenue. At the industry level, the focus of competition in consumer AI has already moved beyond pure model performance benchmarking, with platform channels and commercial scenario integration capabilities becoming increasingly critical. Referring to the mobile internet landscape of iOS and Android, the future AI agent market may concentrate toward leading platforms, and Meta and Alphabet Inc. Class C possess inherent conditions for scaled development. At the same time, unresolved challenges remain in the industry: existing web pages and applications are not yet adapted for AI agents, and the industry has not yet formed a unified consensus between the two major technical routes of browser simulation and API calls. Heavy AI Investment Weighs on Short-Term Financials, Long-Term Earnings Recovery in Sight Meta is bearing enormous capital expenditures for its AI business. Goldman Sachs Group, Inc. predicts that the company's revenue will grow from $200.965 billion in 2025 to $370.837 billion in 2028. However, computing infrastructure investment will weigh on profitability, with free cash flow potentially turning negative in 2027 and only expected to recover in 2028; as economies of scale are unleashed, EBITDA will see accelerated growth, and valuation will gradually be digested as performance grows. Meta still faces many downside risks: intensifying competition in the internet sector; antitrust and regulatory scrutiny that may restrict M&A expansion; the risk that businesses such as the metaverse and social commerce may underdeliver; and if AI capital expenditures suppress profit margins for longer than the market expects, it would likewise hit market confidence. The September Connect developer conference and the release of a new-generation foundation model will become important observation windows. Overall, Muse AI is a key strategic move by Meta to connect AI with consumer scenarios, but at this stage the emphasis is on strategic positioning, and commercialization realization will take time. Investors need to balance the AI technology dividend against the operational pressure brought by heavy investment.