There is no single, consistently reported “AI revenue” total in the NVIDIA and Microsoft filings discussed here. Both companies report broader business categories and explain how AI contributes to growth; neither figure should be relabeled as a standalone AI revenue total. To judge how much growth is actually attributable to AI, check the category’s scope, the company’s own attribution, margins and costs, customer concentration, and fiscal period.
What counts as AI revenue?
A company’s reported AI revenue is directly comparable to another company’s only when both figures have clear, compatible definitions and scopes. The filings discussed here do not provide a harmonized standalone AI revenue line. They instead report segments or end markets and describe AI as a contributor to some results.
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A useful disclosure ladder keeps those claims distinct:
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Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →- AI-specific figure: Use this label when a company reports a defined AI revenue line or provides a transparent calculation for it. The NVIDIA and Microsoft filings discussed here do not supply such a comparable total.
- Reported segment or end-market: Quote the issuer’s label, such as NVIDIA’s Compute & Networking segment or Data Center end market. These are company-defined categories with different scopes, not synonyms for AI revenue.
- AI-attributed growth: Say that management links a reported category’s growth to AI or accelerated computing. That does not mean every dollar in that category came from AI.
- Third-party estimate: Identify the estimator, method, date, and scope. A third-party number is not validated by the company filings alone.
For readers, this distinction answers a common question: “How much of a company’s growth comes from AI?” If the company does not disclose a defined AI figure or a transparent calculation, its broader segment growth cannot tell you exactly how much revenue AI generated.
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What NVIDIA and Microsoft report—and what the numbers mean
The two companies’ figures below refer to different fiscal years and categories. They are examples of how issuers describe AI-related business, not a synchronized ranking or a direct comparison of AI revenue.
| Company and period | Reported figure | What it measures |
|---|---|---|
| NVIDIA, fiscal 2026 ended January 25, 2026 | $215.938 billion total revenue, up 65% year over year | Company-wide revenue, not AI revenue. NVIDIA attributed growth partly to platform shifts including accelerated computing and AI. NVIDIA Form 10-K |
| NVIDIA, fiscal 2026 | $193.479 billion Compute & Networking segment revenue, up 67% | A reported segment. NVIDIA described its increase as driven by platform shifts including accelerated computing and AI; it is not a separately identified AI total. NVIDIA Form 10-K |
| NVIDIA, fiscal 2026 | $193.737 billion Data Center end-market revenue, compared with $115.186 billion in fiscal 2025 | An end-market measure, distinct from the similarly sized Compute & Networking segment. The filing attributes growth to demand for its Blackwell computing platform and related networking systems. NVIDIA Form 10-K |
| Microsoft, fiscal 2025 ended June 30, 2025 | $106.265 billion Intelligent Cloud revenue, up 21% | A reported segment, not a standalone AI revenue line. Microsoft 2025 Annual Report |
| Microsoft, fiscal 2025 | Azure and other cloud services growth of 34% | A cloud-service growth measure. It is not the same category or period as NVIDIA’s Data Center end market or Compute & Networking segment. Microsoft 2025 Annual Report |
Growth rates in this table answer different questions because the categories differ. NVIDIA also reported fiscal 2026 Data Center computing growth of 59% and Data Center networking growth of 142%; those are growth rates for reported Data Center components, not estimates of AI’s share of revenue. NVIDIA Form 10-K
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Can hardware sales make AI growth look bigger?
Hardware sales are real revenue. The issue is interpretation: a rapid increase in large equipment shipments can produce a growth rate that is difficult to compare with a cloud service or mature software subscription. The businesses may recognize revenue at different points in the supply chain, so adding a hardware vendor’s sales to a cloud provider’s revenue can count different stages of related spending rather than distinct end-user AI purchases.
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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteNVIDIA’s fiscal 2026 Data Center end-market revenue illustrates the scale of equipment and related systems sales. Its filing says growth was driven by demand for the Blackwell computing platform and related networking systems. That helps explain the reported category’s momentum, but it does not establish that every dollar in the category—or every dollar of company growth—was generated by AI.
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Cloud services present a different view. AI-related demand may be reflected in broad cloud-service categories, while the cost of building and operating infrastructure affects margins. Microsoft reported 34% growth in Azure and other cloud services, 21% growth in Intelligent Cloud revenue, and a 69% Microsoft Cloud gross margin percentage in fiscal 2025. It linked the margin decline to scaling AI infrastructure, partly offset by Azure efficiency gains. These measures describe cloud growth and its economics; they do not combine into an AI revenue total. Microsoft 2025 Annual Report
Why growth needs a margin and cost check
Revenue growth shows how much sales increased, not whether each dollar of sales became more profitable. NVIDIA’s fiscal 2026 gross margin was 71.1%, down from 75.0% in fiscal 2025. The company cited the transition to Blackwell full-scale data-center solutions and a $4.5 billion H20 inventory and purchase-obligation charge. Those details show why a fast-growing hardware category should be read alongside margins and costs. NVIDIA Form 10-K
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For cloud providers, the relevant question is whether service growth is accompanied by infrastructure costs that pressure margins. Microsoft’s fiscal 2025 report linked the decline in Microsoft Cloud gross margin percentage to scaling AI infrastructure, with Azure efficiencies partly offsetting the effect. Microsoft 2025 Annual Report
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- Identify the scope. Is the figure a standalone AI product or service, a broad cloud segment, a data-center end market, hardware sales, or management’s explanation of a growth driver? Preserve the company’s label.
- Check the revenue type and timing. Distinguish equipment shipments from subscriptions, consumption-based services, or other contract revenue. Do not assume they are recognized at the same point in a customer’s spending cycle.
- Read growth with economics. Look for gross margin, cost of revenue, inventory charges, and capital spending alongside sales growth. A rising revenue figure alone does not establish improving profitability.
- Check attribution and concentration. Ask whether the company identifies direct buyers, resellers or channel partners, or estimated end users. NVIDIA said two direct customers represented 22% and 14% of its fiscal 2026 total revenue, and cautioned that indirect-customer revenue is estimated and can differ from actual results. NVIDIA Form 10-K
- Align periods and geography. NVIDIA’s fiscal 2026 ended January 25, 2026; Microsoft’s fiscal 2025 ended June 30, 2025. NVIDIA reports geography based on direct customers’ headquarters and cautions that an end customer’s location can differ from the shipping location. A comparison should preserve both the fiscal-year and geographic definitions. NVIDIA Form 10-K Microsoft 2025 Annual Report
What investors can—and cannot—conclude
The filings establish that NVIDIA reported rapid growth in specified segments and end markets while attributing some of that growth to AI-related demand, and that Microsoft reported growth in cloud categories while discussing the infrastructure costs associated with scaling AI. They do not establish a single comparable AI revenue total across the two companies, a market-wide AI revenue figure with a common scope, or the exact share of either company’s broader category generated by AI.
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For personal investors, the practical approach is to treat “AI revenue” as company-specific unless the issuer defines and reconciles the figure. Compare like with like, keep hardware and service categories separate, and read growth alongside margins, costs, customer concentration, and the relevant fiscal period.
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