Microsoft’s biggest transformation story used to revolve around cloud computing.
In many ways, the Redmond, Wash.-based technology giant has rewired enterprise infrastructure from the ground up, or from the cloud, by moving companies from on-premises software to subscription services and hyperscale infrastructure.
But if Microsoft’s fiscal 2026 second-quarter earnings call on Wednesday (January 28) is any indication, the company’s latest transformation story now revolves around artificial intelligence (AI).
“We’re still in the early stages of AI adoption, but Microsoft is already building an AI business bigger than some of the biggest franchises,” Microsoft Chairman and CEO Satya Nadella told investors, according to the company’s earnings call. “We’re pushing the frontiers across the AI stack and creating new value for our customers and partners.”
The clearest sign of Microsoft’s AI strategy came in its intelligent cloud segment. Revenue there grew 29% year over year to $32.9 billion, with Azure and other cloud services increasing 39% on a reported basis. Although Microsoft doesn’t explicitly announce AI revenue, Azure has become the primary delivery mechanism for large-scale AI workloads, from training foundational models to deploying inference at enterprise scale.
“Microsoft Cloud revenue exceeded $50 billion in the quarter, reflecting strong demand for our service portfolio,” Microsoft Executive Vice President and CFO Amy Hood said in the earnings call.
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In the second quarter, the company’s overall reported revenue increased 17% year-over-year to $81.3 billion, and Microsoft’s operating income increased 21% to $38.3 billion.
Despite beating analyst estimates, the tech company’s stock fell to mid-single digits in after-hours trading on concerns over AI-driven capital spending, which rose 66% in the quarter.
Asked about the move during an investor Q&A, Nadella and Hood emphasized that short-lived assets, primarily GPUs and CPUs, “have already been sold over their entire useful life.”
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Microsoft’s AI advantage is no longer theoretical or cheap
That’s because Microsoft aims to control the entire AI stack, executives told investors in response to questions about capital spending. Azure doesn’t just rent GPUs. Increasingly, model access, orchestration tools, security, and governance are bundled into a single enterprise-ready environment. This reduces friction for customers who need AI capabilities without managing fragmented vendor relationships.
The result is a flywheel. AI demand is driving the use of Azure, which in turn justifies further infrastructure investment and strengthens Microsoft’s scale advantage.
Microsoft’s remaining commercial performance obligations have increased by 110% and now stand at $625 billion, highlighting just how persistent this demand is. Companies aren’t experimenting with AI on short-term contracts. They are working on long-term capabilities.
Microsoft retains 80% of its OpenAI model revenue with Azure customers, but retains a portion of Anthropic’s AI model revenue, according to the company’s financial reports.
Still, pursuing AI leadership is expensive. Microsoft’s balance sheet reflects a dramatic expansion in property, plant and equipment, increasing net assets to $261 billion. While operating cash flow remains strong, free cash flow is increasingly shaped by infrastructure investment decisions that can take years to pay back.
It was discussed how Microsoft is part of a small group of technology giants expected to spend a total of more than $500 billion in capital spending in 2026, driven primarily by investments in data centers, chips, and AI infrastructure. Microsoft’s capital expenditures for the most recent quarter, including assets acquired under finance leases, were $37.5 billion.
Training large models requires large capital expenditures on specialized hardware, but inference workloads result in continuous high-return consumption over time.
The company is in the early stages of what Nadella calls the AI adoption phase, which favors platforms over point solutions. Microsoft’s ability to deliver AI as infrastructure, applications, and services could position it well, and the company’s accelerating investments in data centers signals confidence that demand for AI-driven computing may remain structurally higher than traditional cloud demand.
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Rethinking productivity
One aspect of Microsoft’s AI strategy that is often overlooked is governance. The company repeatedly emphasizes responsible deployment, security, and compliance as not just ethical practices, but commercial imperatives. Large companies and governments are unlikely to deploy AI at scale without guarantees around data protection, explainability, and regulatory alignment.
This governance supports the company’s Microsoft 365 Productivity and Business Processes business, which saw revenue increase 16% to $34.1 billion in the quarter due to strong performance across its commercial and consumer cloud products. Microsoft 365 commercial cloud revenue increased 17% and consumer cloud revenue increased 29%.
Dynamics 365 revenue increased 19%. This reflects how AI is reshaping business applications. Predictive forecasting, automated workflows, and conversational interfaces are playing an increasingly important role in the customer relationship management (CRM) and enterprise resource planning (ERP) systems used by finance leaders.
The PYMNTS Intelligence report, “Smarter Spending: How AI is Transforming Financial Decision-Making,” found that more than 8 in 10 CFOs at large companies are already using or considering implementing AI.
