AI monetization is just the beginning? Morgan Stanley sharply raises Meta's target price: Q2 ad revenue expected to surpass Google Search for the first time.

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Morgan Stanley points out that Meta's current stock price does not fully reflect the potential value of its AI transformation, and its growth logic is undergoing a qualitative leap. If the previous rise was driven by cost reduction in the "Year of Efficiency", the next stage of growth will be entirely driven by core returns on invested capital (ROIC) brought by AI.

According to Wind Trading Desk, on January 29, Morgan Stanley's Brian Nowak analysis team sharply raised Meta's target price from $750 to $825 in their report, implying about 15% upside from the current level.

Morgan Stanley's report not only raised 2027 earnings per share (EPS) expectations by 10%, but also made the prediction: Meta's advertising revenue is expected to surpass Google Search for the first time in Q2 2026, ending Google's long-term dominance in the digital advertising space.

The confidence behind all this comes from Mark Zuckerberg sending clear signals to investors on the conference call: Meta is using large models to completely rewrite its recommendation system, and he considers the current system still "primitive". Morgan Stanley believes that if the current system is still primitive, long-term opportunities and improvements are likely to bring even more growth. They expect further improvements for Meta in personalization (as META is able to analyze more data more efficiently), agent services (such as MetaAI), new creative/media services for users/advertisers, wearable devices, etc. This is not just a tech upgrade, but a generational leap from “traffic monetization” to the infrastructure for "personal superintelligence."

Historic Moment: Meta’s Ad Revenue Will Surpass Google Search in Q2

The most striking forecast in the research report is the comparison between the two giants' ad businesses. Morgan Stanley points out that although Google is also accelerating its execution, the engagement and monetization driven by AI at Meta is even more stunning. For reference, they note that when Google's search business hit $57 billion in quarterly revenue, its annual growth rate was 15%; when Meta reached the same scale, its growth rate was as much as 34%-35%.

Based on Morgan Stanley’s current modeling, Meta’s quarterly advertising revenue will officially surpass Google Search’s ad revenue in Q2 2026, and the gap will widen further thereafter. This forecast not only marks an enhancement of Meta's dominance in the ad market but also demonstrates the absolute superiority of its AI-driven recommendation algorithms in capturing user attention and advertiser budgets.

Zuckerberg’s “Versailles moment”: Recommendation Systems Are Being Rewritten by Large Models; Current Systems Still “Primitive”

On the call, Zuckerberg’s remarks provided the technical underpinning for Morgan Stanley’s bullish view. He said that while Meta’s world-class recommendation system has already driven Instagram Reels viewing time up over 30% year-on-year in the US, the current system is still very “primitive” compared to the technological changes to come.

Meta is undertaking a massive project: turning its whole recommendation system into a scalable engineering system similar to large language models (LLM). The current system is efficient, but will soon be replaced by large models capable of understanding users’ unique goals, backgrounds, and interests. Such a reconstruction of the technical architecture will not only determine user time spent on the platform, but also directly determine ad pricing and conversion rates. Data shows that just by simplifying the ranking architecture, Facebook increased the browsing volume of organic feeds and video posts by 7% in Q4, and management called this the biggest product optimization boosting revenue in the past two years.

The Tangibility of AI Monetization: From Reels to Comprehensive Conversion Rate Improvement

Morgan Stanley’s report breaks down in detail how Meta converts AI technology and computing power into real money. This is not an empty concept, but is reflected in every key operational metric:

On the engagement side: Through more efficient model scaling, Instagram Reels’ watch time has surged over 30% year-on-year; by simplifying its ranking architecture, Facebook increased the view count for organic feeds and video posts by 7%, the biggest revenue boost from product optimization in the last two years.On the ad side: Meta expanded the coverage of its ad ranking model GEM to all Reels, supported by double the GPU units for training. As a result, Facebook ad clicks increased by 3.5%, and Instagram conversion rates improved by over 1%.On the efficiency side: Introducing new runtime models improved Instagram conversion rates by 3%; company-wide adoption of internal AI coding tools increased engineering productivity by 30% in 2025, with output for some advanced users even surging by 80%.

Capital Expenditure and Infrastructure: Paying for the Future

In response to market concerns about capital expenditure, Morgan Stanley’s report provides clear expectations. Meta’s 2026 capital expenditure guidance ranges from $115 billion to $135 billion, mainly targeting superintelligence labs and core business infrastructure. Morgan Stanley’s modeling forecasts infrastructure expenditures (including cloud spending, depreciation, etc.) will increase by about $36 billion and drive about 75% of 2026’s operating expense growth.

Although the investment is huge, Morgan Stanley believes it is the necessary price for “sustained growth.” Meta made it clear there are still capacity bottlenecks, with demand growing faster than supply. To solve this, Meta is not only aggressively purchasing chips (including from NVIDIA, AMD, and their self-developed MTIA), but also building an Andromeda architecture that can operate across chips. For investors, as long as revenue growth outpaces investment costs—as Morgan Stanley predicts—this kind of high-intensity capital expenditure is reasonable, and is building Meta a virtually unassailable AI moat.

Risk Notice and DisclaimerThe market involves risk, and investment should be cautious. This article does not constitute personal investment advice and has not considered the investment goals, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article suit their own circumstances. Investment is at your own risk.

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