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“AI revenue” is not a consistently defined line item across company filings. NVIDIA reports broad segments and end markets that management says benefited from AI demand; Microsoft reports cloud categories where AI-related services and infrastructure costs are part of a larger business. Those figures can show where AI is influencing growth, but they are not directly comparable totals of revenue generated by AI.
To judge an AI growth claim, first identify what the company actually counted, then examine the period, revenue mix, margins, costs, and customer disclosures. Hardware shipments can rise sharply as customers expand capacity, while cloud services may earn revenue through a different model and over a different period. That difference can make growth rates look unlike-for-like.
What counts as AI revenue?
A useful way to read an AI revenue claim is to place it on a disclosure ladder. The label matters: a figure for a broad segment or end market is not automatically an AI-specific sales total.
- Directly reported AI-specific revenue: Use this only when a company defines an AI revenue line or provides a transparent calculation. The NVIDIA and Microsoft filings discussed here do not provide a harmonized standalone AI revenue total.
- Reported segment or end-market revenue: Preserve the company’s exact label, such as NVIDIA’s Compute & Networking segment or Data Center end market. Their scopes differ, and neither should be silently renamed “AI revenue.”
- AI-attributed growth: A company may say AI helped drive growth in a reported category. This describes management’s explanation for performance; it does not mean the entire category’s revenue came from AI.
- Third-party estimate: Treat an outside estimate as a separate measure. To assess it, identify the estimator, method, date, and scope rather than presenting it as a company-reported figure.
The practical distinction is between what a filing measures and what management says influenced that measure. NVIDIA says platform shifts including accelerated computing and AI drove growth in Compute & Networking. That is an explanation of the segment’s growth, not a calculation of AI-only sales.
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What NVIDIA and Microsoft actually report
The latest fiscal-year figures in the cited filings illustrate why the categories should not be combined into a single ranking. NVIDIA’s fiscal 2026 ended January 25, 2026; Microsoft’s fiscal 2025 ended June 30, 2025. The periods are not synchronized.
| Company and fiscal period | Reported measure | What it says—and does not say |
|---|---|---|
| NVIDIA, fiscal 2026 | Total revenue: $215.938 billion, up 65% year over year | Company-wide revenue; not an AI-only total. NVIDIA fiscal 2026 Form 10-K. |
| NVIDIA, fiscal 2026 | Compute & Networking: $193.479 billion, up 67% | A reported segment. NVIDIA attributes growth partly to platform shifts including accelerated computing and AI; the segment is not labeled AI revenue. NVIDIA fiscal 2026 Form 10-K. |
| NVIDIA, fiscal 2026 | Data Center end-market: $193.737 billion, versus $115.186 billion in fiscal 2025 | A separately reported end-market measure, distinct from the similarly sized Compute & Networking segment. Do not add or substitute the two figures as though they were separate AI sales totals. NVIDIA fiscal 2026 Form 10-K. |
| Microsoft, fiscal 2025 | Intelligent Cloud: $106.265 billion, up 21% | A broad business segment, not a standalone AI revenue figure. Microsoft 2025 Annual Report. |
| Microsoft, fiscal 2025 | Azure and other cloud services: growth of 34% | A cloud-services growth measure; it does not disclose how much of that growth was AI-generated. Microsoft 2025 Annual Report. |
NVIDIA also reported fiscal 2026 Data Center computing growth of 59% and Data Center networking growth of 142%, and said demand for its Blackwell platform and related networking systems drove Data Center growth. Those rates describe different parts of the reported business; neither is a company-wide AI revenue growth rate. NVIDIA fiscal 2026 Form 10-K.
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Why hardware sales can make growth look unusually fast
Large equipment shipments can expand quickly when customers build data-center capacity. That is real revenue, but a surge in shipments can produce a growth rate that is difficult to compare with recurring software subscriptions or cloud services billed as customers consume them. The revenue measures also sit at different points in a supply chain: a hardware vendor’s sale and a cloud provider’s later service revenue should not automatically be added as separate end-user AI spending.
That overlap is especially important when companies sell to cloud providers or other intermediaries. A vendor may recognize revenue from a direct customer while a service provider later earns revenue from customers using the equipment. Those are distinct transactions, not necessarily distinct measures of final AI demand. The cited filings do not provide a common market-wide total that resolves such overlap.
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- ✅Supports Linux and Windows. Supports the temperature range of -40°C to 85°C
In NVIDIA’s fiscal 2026 filing, Data Center end-market revenue was $193.737 billion, and the company linked growth to Blackwell computing and networking demand. That scale indicates the importance of data-center demand to reported results, but it does not establish that every dollar in the category is AI-only revenue.
Check margins and costs, not just sales growth
Revenue growth alone does not show whether the economics of that growth are improving. In fiscal 2026, NVIDIA’s 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. The figures show why investors should read margin and cost explanations alongside sales growth rather than assume that a larger revenue base means unchanged profitability. NVIDIA fiscal 2026 Form 10-K.
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Cloud businesses face a different mix of revenue and cost. Microsoft reported a Microsoft Cloud gross margin percentage of 69% for fiscal 2025 and linked the decline to scaling AI infrastructure, partly offset by Azure efficiencies. This measure is not directly interchangeable with NVIDIA’s company gross margin: it covers a different business and fiscal period. Microsoft 2025 Annual Report.
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The cited filings do not let readers calculate exactly how much of NVIDIA’s or Microsoft’s broader reported revenue came from AI. NVIDIA’s disclosures describe AI and accelerated computing as drivers of growth in reported categories; Microsoft’s cloud disclosures describe growth and the cost of scaling AI infrastructure, but do not isolate an AI revenue total. There is no common AI revenue definition or market-wide total in these filings.
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Customer and channel disclosures add another qualification. NVIDIA said two direct customers represented 22% and 14% of its fiscal 2026 total revenue. It also said revenue from indirect customers is estimated and may differ from actual results. Direct-customer concentration can indicate reliance on a small number of buyers, but it does not identify how much of their purchases ultimately served AI workloads. NVIDIA fiscal 2026 Form 10-K.
Geographic comparisons require similar care: NVIDIA reports geography based on the headquarters of direct customers and cautions that the end customer’s location and the shipping destination can differ. A reported regional figure therefore should not be read as a precise measure of where equipment is ultimately used. NVIDIA fiscal 2026 Form 10-K.
Quick Recap
A practical checklist for comparing AI growth claims
- Scope: Is the figure standalone AI revenue, a hardware product, a cloud service, a segment, an end market, or management-attributed growth?
- Revenue type and timing: Is it equipment shipment revenue, subscription revenue, consumption-based service revenue, or another contract category? Compare timing only when the company’s accounting disclosures support it.
- Growth quality: Read gross margin, cost of revenue, inventory charges, and capital spending alongside the sales figure.
- Attribution: Check whether sales are to direct customers, resellers, or estimated end users, and note any disclosed customer concentration.
- Period and geography: Align fiscal-year ends and year-over-year periods. Check how the company defines geography before comparing regions.
- Overlap: Before adding a hardware vendor’s revenue to a cloud provider’s, ask whether the figures reflect separate end-user spending or successive transactions in the same supply chain.
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