Two of the world’s largest technology companies, Microsoft and Meta Platforms, have revealed massive capital expenditure plans for 2026, underscoring their commitment to dominating the artificial intelligence landscape. Microsoft expects to spend around $190 billion this calendar year, while Meta has earmarked up to $145 billion for servers, data centers, and networking infrastructure. The announcements came alongside strong quarterly earnings that showed accelerating revenue growth, particularly in cloud and advertising segments driven by AI adoption.
Microsoft’s fiscal third quarter saw revenue rise 18% year-over-year to $82.9 billion, with Azure cloud growing 40%. The company’s AI business reached an annual revenue run rate of $37 billion, up 123%, and paid Microsoft 365 Copilot seats crossed 20 million. Despite the robust top-line numbers, management warned that cloud gross margin would dip to around 64% next quarter as AI investments weigh on profitability. Wall Street remains overwhelmingly bullish, with 48 analysts maintaining a consensus Moderate Buy and a 12-month price target implying 45% upside.
Meta reported Q1 2026 revenue of $56.31 billion, a 33% jump fueled by AI-enhanced ad targeting that pushed ad impressions up 19% and average price per ad up 12%. The company plans to deploy 7 gigawatts of computing capacity this year, doubling to 14 GW in 2027, partly by developing custom AI chips with Broadcom and TSMC to reduce reliance on Nvidia. However, Reality Labs continues to bleed cash, losing over $4 billion in the quarter on just $402 million in revenue. Analysts remain largely constructive, with a Moderate Buy consensus and an average price target of $838.26.
The spending spree highlights a broader industry trend: big tech is racing to build out infrastructure for a future where AI is embedded in everything from cloud services to social media feeds. For the crypto market, these moves may indirectly boost AI-related blockchain projects, though no immediate direct impact on specific tokens is evident. The scale of investment signals long-term confidence in AI’s transformative potential, but near-term margin pressures and execution risks remain key uncertainties.
