Microsoft and Meta Earnings Shift Focus to Returns on AI Spending

As the first major technology companies prepare to report earnings later today (Jan. 28), attention is shifting from how much Big Tech is spending on artificial intelligence (AI) to whether those investments are starting to pay off. Earnings from Microsoft and Meta Platforms are expected to test whether that spending is translating into durable growth and profitability.

According to Bloomberg, Microsoft and Meta are part of a small group of technology giants expected to spend more than $500 billion combined on capital expenditures in 2026, largely driven by investments in data centers, chips and AI infrastructure. That figure represents a sharp increase from 2025 and has intensified scrutiny of margins, cash flow and the pace at which AI-driven products can be monetized.

Microsoft’s results are expected to provide signals on whether artificial intelligence features embedded across Azure and its software portfolio are translating into sustained cloud growth. Bloomberg notes that the focus has shifted beyond headline revenue growth to whether AI is helping Microsoft defend margins while absorbing rising infrastructure costs.

Meta has been explicit about its aggressive investment strategy, committing tens of billions of dollars to AI compute and model development. Bloomberg reports that while Meta’s revenue growth remains solid, questions are emerging about how quickly those investments can contribute to profits, particularly as expenses continue to rise.

As PYMNTS previously covered, impatience is growing around Meta’s expanding AI budget. The company recently paid $2 billion for Singapore-based startup Manus to boost its artificial intelligence agent offerings.

CNBC framed the current reporting season as a turning point in how AI spending is evaluated. After several quarters in which markets largely rewarded companies for committing capital to AI, the emphasis is now on how executives explain the link between that spending and financial performance.

Bloomberg notes that depreciation and operating costs linked to new data centers and specialized AI hardware are rising faster than in previous cloud investment cycles. Upcoming earnings are likely to reinforce question on how quickly AI-powered services can scale, whether cloud growth can offset higher depreciation and energy costs, and how disciplined companies will be in managing capital expenditures if economic conditions soften.

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