By migrating enterprises from on-premise software to subscription services and hyperscale infrastructure, the Redmond, Washington-based tech giant in many senses rewired corporate infrastructure from the ground-up, or the cloud-down.
But if Microsoft’s second quarter fiscal 2026 earnings call Wednesday (Jan. 28) is any indication, the company’s latest transformation story now revolves around artificial intelligence (AI).
“We are only at the beginning phases of AI diffusion and already Microsoft has built an AI business that is larger than some of our biggest franchises We are pushing the frontier across our entire AI stack to drive new value for our customers and partners,” Satya Nadella, chairman and CEO of Microsoft told investors, according to the earnings release.
The clearest signal of Microsoft’s AI strategy appeared in its Intelligent Cloud segment. Revenue there rose 29% year over year to $32.9 billion, with Azure and other cloud services growing 39% in reported terms. While Microsoft does not break out AI revenue explicitly, Azure has become the primary delivery mechanism for large-scale AI workloads, from training foundation models to deploying inference at enterprise scale.
“Microsoft Cloud revenue crossed $50 billion this quarter, reflecting the strong demand for our portfolio of services,” Amy Hood, Microsoft executive vice president and CFO, said in the earnings release.
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The company’s overall reported revenue for the second quarter reached $81.3 billion, up 17% year over year, while Microsoft’s operating income climbed 21% to $38.3 billion.
Despite topping analyst estimates, the tech firm’s share price fell mid-single-digits in after-hours trading due to concerns around AI-driven capital expenditures, which were up 66% for the quarter.
Asked about the movement during the investor Q&A, both Nadella and Hood stressed that the short-lived assets, primarily GPUs and CPUs, are “already sold for their entire useful life.”
More here: AI Doers Drown Out AI Naysayers
Microsoft’s AI Advantage Is No Longer Theoretical, Nor Is it Cheap
As executives told investors in response to questions about capital expenditures, the reason is that Microsoft is aiming to control the full AI stack. Azure is not just renting GPUs; it is increasingly bundling model access, orchestration tools, security and governance into a single enterprise-ready environment. This reduces friction for customers who want AI capabilities without managing fragmented vendor relationships.
The result is a flywheel: AI demand drives Azure usage, which in turn justifies further infrastructure investment, reinforcing Microsoft’s scale advantage.
Microsoft’s 110% increase in commercial remaining performance obligation, which now stands at $625 billion, underscores how sticky this demand has become. Enterprises are not experimenting with AI on short contracts; they are committing to long-term capacity.
Per the company’s financials, while Microsoft keeps 80% of sales of OpenAI models to Azure customers, it retains a smaller percentage of its sales of Anthropic’s AI models.
Still, chasing AI leadership is expensive. Microsoft’s balance sheet reflects a dramatic expansion in property and equipment, with net assets rising to $261 billion. Cash flow from operations remains robust, but free cash flow is increasingly shaped by infrastructure investment decisions that may take years to pay off.
It was covered here how Microsoft is 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. Microsoft’s capital expenditures including assets acquired under finance leases were $37.5 billion for the most recent quarter.
Training large models requires massive capital expenditure in specialized hardware, while inference workloads create persistent, high-margin consumption over time.
The company is still early in what Nadella called the diffusion phase of AI, and diffusion favors platforms over point solutions. Microsoft’s ability to deliver AI as infrastructure, application and service could position it favorably, and the company’s accelerating investments in data centers signal confidence that demand for AI-driven compute may remain structurally higher than traditional cloud demand.
See also: Enterprise AI Gets Real as Davos 2026 Focuses on Agents
Productivity Reimagined
One often overlooked aspect of Microsoft’s AI strategy is governance. The company repeatedly emphasizes responsible deployment, security and compliance not merely as ethical commitments, but as commercial necessities. Large enterprises and governments are unlikely to adopt AI at scale without assurances around data protection, explainability and regulatory alignment.
That governance supports the company’s Microsoft 365 Productivity and Business Processes business, where revenue grew 16% to $34.1 billion for the quarter, driven by strong performance across commercial and consumer cloud offerings. Microsoft 365 Commercial cloud revenue increased 17%, while consumer cloud revenue jumped 29%.
Dynamics 365 revenue rose 19%, reflecting how AI is also reshaping business applications. Predictive forecasting, automated workflows and conversational interfaces are increasingly table stakes in the customer relationship management (CRM) and enterprise resource planning (ERP) systems that finance leaders use.
The PYMNTS Intelligence report “Smart Spending: How AI Is Transforming Financial Decision Making” found that more than 8 in 10 CFOs at large companies are either already using AI or considering adopting it.
