Daniel Loeb Adds Meta and Alphabet as Big Tech Steps Up AI Spending

Billionaire investor Daniel Loeb’s Third Point LLC added new exposure to two of the largest AI infrastructure investors in the market, Meta Platforms and Alphabet, according to a report summarizing the fund’s first-quarter FY26 moves. The update said Loeb acquired 90,000 shares of Meta and 175,000 shares of Alphabet during the quarter, placing bets on companies that are spending heavily to expand the data centers and server capacity needed to train and serve generative AI systems. The trades come amid renewed investor attention on whether the industry’s multi-year “compute buildout” can translate into durable revenue and profit.

Meta and Alphabet are both moving money toward AI hardware and facilities, but they differ in how investors track that spending. Capital expenditures, or capex, is the line item companies use for major purchases such as servers, networking equipment, and data center construction, often including payments tied to finance leases. Meta’s most recent outlook said it expects 2026 capex, including principal payments on finance leases, to rise to $125 billion to $145 billion, up from its prior forecast range. In explaining the increase, Meta cited higher component pricing and additional data center costs tied to future capacity.

Alphabet similarly tied its spending outlook to AI demand and supply constraints. In a Q4 2025 earnings call transcript, Alphabet said its “2026 CapEx investments” are anticipated to be in the range of $175 billion to $185 billion. Management framed the spending as investments in AI compute capacity, including work supporting frontier model development at Google DeepMind, ongoing improvements across products and services, and significant customer demand for Google Cloud. Alphabet also acknowledged that reported capex can vary with the timing of supply and cash payments.

For Alphabet, the funding push is showing up in the company’s reported operating performance as well as its forward-looking spending plan. In an SEC-filed first-quarter 2026 results release, Alphabet reported revenues of $109.9 billion, up 22% year over year, and operating income of $39.7 billion, reflecting operating margin expansion to 36.1%. The filing also highlighted that Google Cloud revenues grew 63% year over year to $20.0 billion, a figure the company linked to enterprise AI infrastructure and related offerings.

Meta’s latest quarter also underscored the backdrop for investor repositioning. In its first-quarter 2026 earnings press release, Meta reported revenue of $56.31 billion, up 33% year over year, and said capital expenditures, including principal payments on finance leases, were $19.84 billion for the quarter. The same filing gave the capex guidance range for the full year and reiterated that the increase reflects component costs and additional data center costs to support future capacity. Meta’s results and guidance are part of how investors benchmark AI spend against advertising and messaging-driven revenue growth.

Third Point’s additions do not, on their own, provide a detailed rationale for why Loeb chose Meta and Alphabet specifically, nor do they quantify the stakes beyond the share counts cited in the report. In the U.S., these changes typically derive from quarterly 13F disclosures, which generally show positions at quarter-end but do not capture the full complexity of an investor’s exposure, such as derivatives, short positions, or intraday trading. That means the trades can be read as a directional announcement of interest, but not as proof of a specific thesis about near-term AI monetization.

What to watch next is whether both companies can convert high capex into improved margins and cash generation as AI products scale. For Alphabet, investors will look for continued acceleration in Google Cloud and sustained momentum in AI-driven user engagement while capex remains elevated. For Meta, the key question is whether infrastructure spending and AI product development translate into stronger ad performance, engagement, and efficiency gains before the market judges the return on that infrastructure buildout. As with any heavy-spend cycle, the timing of component deliveries, data center construction, and the pace of AI commercialization will shape quarterly results.