Wednesday marked a pivotal day for the tech industry as Meta, Google, Amazon, and Microsoft all reported earnings simultaneously. Among the four, Meta emerged as the clear underperformer, with its shares dropping more than 7% despite a 33% revenue surge—the company's fastest growth since 2021. The decline stemmed from Meta's announcement that its 2026 capital expenditures would be at least $10 billion higher than previously forecast, potentially reaching $145 billion. CEO Mark Zuckerberg attributed the increase primarily to rising component costs, especially memory chip pricing, driven by the global AI boom.
This spending spree reflects the unprecedented data center buildout underway across the tech industry. The demand for advanced memory chips—essential for training and running large AI models—has constrained global supply, triggering a memory crisis that affects not only AI firms but also consumer electronics like laptops and smartphones. Meta's $145 billion projection is a dramatic leap from the $72 billion it spent just last year, underscoring the company's aggressive pivot toward artificial intelligence after falling behind rivals like Google.
The AI Catch-Up Strategy
Zuckerberg acknowledged Meta's lagging position roughly ten months ago, announcing a major turnaround effort. The company committed billions to research and development and began poaching top talent from across the industry, including recruiting Scale AI founder Alexandr Wang to lead the newly formed Meta Superintelligence Labs. This division recently unveiled its first major product: Muse Spark, a proprietary AI model that Meta plans to open-source in the future. While experts view this as a positive step, they caution that Meta still has significant ground to cover before it can claim success in the AI race.
During the earnings call, Zuckerberg assured investors that the work at Meta Superintelligence Labs is on track. “This was the first release from Meta Superintelligence Labs, and it shows that our work is on track to build a leading lab,” he said. “Now that we have a strong model, we can develop more novel products as well.” He outlined plans to release two AI agents: one for personal use and another for business applications. Early testing of business AIs has shown weekly conversations growing tenfold since the start of 2025, signaling strong user engagement.
Internal AI Integration and Workforce Changes
Meta is also embedding AI into its core operations. CFO Susan Li revealed that over half a billion weekly users on Facebook and Instagram now watch videos translated and dubbed by AI. The company is leveraging its new AI models to hyper-personalize feeds and improve ad targeting. “Since our recommendation systems are operating at such large scale, we’ll phase in this new research and technology over time,” Zuckerberg noted. “But the trend over the last few years seems clear that we are seeing an increasing return on the amount that we can improve engagement for people and value for advertisers.”
Paradoxically, the AI push is also driving job cuts. Meta announced layoffs affecting 10% of its workforce, with voluntary buyouts offered to 7% of U.S. staff. This follows a broader Silicon Valley trend of using AI to automate tasks and reduce headcount. Executives declined to directly link the layoffs to automation, but Li stated that a “leaner operating model” would help offset the substantial investments in AI infrastructure.
The Ghost of the Metaverse
Investors remain nervous about Meta's willingness to pour billions into speculative technology, given the massive losses from its earlier bet on the metaverse. The Reality Labs division, which led the metaverse efforts, reported an operating loss of over $4 billion in the latest quarter, on just $402 million in revenue. Cumulative losses for that division now exceed $80 billion over six years. While experts are somewhat more optimistic about the AI investments—because they tie directly to Meta's existing advertising business—the scale of spending raises questions about long-term profitability.
The memory chip crisis, exacerbated by AI data center demand, has become a critical factor. Higher component costs, particularly for dynamic random-access memory (DRAM) and high-bandwidth memory (HBM), are squeezing margins across the tech industry. For Meta, these costs are a primary driver of the $145 billion cap ex figure. The company is also competing with other hyperscalers like Google, Microsoft, and Amazon for limited chip supply, further inflating prices.
Looking ahead, Meta's success will depend on whether its AI models can deliver tangible returns—through better ad performance, new product features, or direct revenue from AI agents. The company is also exploring ways to monetize its AI capabilities beyond advertising, though details remain scarce. With the memory shortage unlikely to ease soon, Meta's spending trajectory seems set to continue, making the next few quarters critical for proving the value of its enormous bet.
Source: Gizmodo News