Meta Platforms shares came under pressure after the company’s latest results, even as a prominent Wall Street analyst reiterated a bullish long-term view. Mark Mahaney of Evercore said Meta remains undervalued based on improving advertising demand and AI-driven ad improvements, but he trimmed his price target following a “miss” in earnings.
Key takeaways
- Price move: Meta shares fell about 10% in a single day after its underwhelming earnings report.
- Catalyst: Higher-than-expected AI and infrastructure spending contributed to results that missed analyst estimates.
- Analyst view: Evercore’s Mark Mahaney kept a constructive stance and lowered his price target from $930 to $820.
- Key implication: Investors are likely to keep weighing revenue momentum against the pace and timing of Meta’s AI model progress and capital intensity.
What drove the move
Evercore analyst Mark Mahaney had initially highlighted Meta as a top large-cap long idea on July 22, arguing that advertising demand and ad improvements supported by artificial intelligence would sustain revenue growth. He also said the stock looked inexpensive relative to forward earnings.
That positive framework met near-term headwinds after Meta reported results that came in below expectations. According to the article, Meta posted second-quarter revenue of $60.8 billion, up 28% year over year, but costs rose sharply as the company pushed deeper into AI infrastructure.
The earnings miss appears to have been driven by spending: Meta’s costs and expenses increased 55% year over year to $42 billion in the second quarter, and earnings per share were $6.18, a 13% year-over-year decline and below the $7.14 analyst expectation cited in the report.
Market reaction: valuation support meets capex concerns
Despite the earnings setback, the valuation case remained central to Mahaney’s argument. Data in the article indicates Meta trades at about 17 times forward earnings, making it one of the cheaper mega-cap technology names within the so-called “Magnificent Seven,” second only to Alphabet on the multiple basis referenced by the report.
However, investors focused on the durability and timing of Meta’s AI investments. The company “slightly” raised 2026 capital expenditure guidance to a range of $130 billion to $145 billion, with the prior low end referenced as $125 billion, signaling continued investment rather than a cooldown.
Separately, the report notes that management has provided limited specificity on the progress of its frontier AI models and that Meta has delayed multiple AI rollouts, including Avocado and Muse Spark. In the wake of a sharp earnings move, those delays have tended to elevate uncertainty about how quickly AI spending translates into monetizable product improvements.
Why the bullish thesis still has supporters
While AI spending is a clear concern, the article argues that the business growth case remains intact. Meta’s ad performance appears to be improving: ad impressions rose 14% year over year, and the report states that AI has reportedly begun contributing to higher ad impressions and more revenue per ad.
Mahaney’s view, as presented in the article, also leans on the idea that Meta is benefiting from its large and entrenched user base. It cited that Meta’s platforms averaged 3.6 billion daily active users across its brands in June 2026, one of the largest among tech companies.
The report further notes that the Street is broadly constructive, with analysts’ median one-year price target of $800, close to Mahaney’s revised $820 target. Even so, the article characterizes Meta’s near-term trading as likely to remain volatile given the magnitude of capex and the risk that AI model execution may not match investor expectations.
Bigger picture: capex intensity and execution risk
Meta’s current setup places investors at the intersection of two competing forces: sustained advertising growth versus escalating AI capital intensity. For large-cap technology investors, the key question is whether Meta’s AI investments lead to faster monetization—such as improved ad targeting and performance—or whether spending rises faster than near-term returns.
The report also frames Meta’s situation in contrast with other AI-focused infrastructure buyers, noting that it does not currently have a comparable business to sell computing capacity to customers, unlike hyperscalers that monetize their data-center buildouts through external services.
As a result, the market’s sensitivity to execution timing is likely to remain high. Any additional clarity on frontier AI model delivery, product rollouts, and measurable monetization outcomes could influence how investors view both the earnings trajectory and the long-term valuation floor suggested by forward earnings multiples.
Investors may look next for updated guidance signals from Meta around capex and AI-related milestones, along with subsequent quarterly results that show whether ad impressions gains are translating into stronger profitability. Additional catalysts include future earnings updates and broader market expectations for technology spending amid the AI buildout, which can amplify reactions to both upside and downside surprises.
