NetApp Reports Strong Quarter, Signals AI Infrastructure Spending Is Moving From Pilot to Production
NetApp beat earnings expectations and raised its fiscal 2027 outlook, citing broad-based enterprise demand for AI infrastructure. The company reported non-GAAP earnings of $2.43 per share against a consensus estimate of $2.27, and revenues of $1.95 billion versus $1.86 billion expected.
Chief executive George Kurian framed the results as evidence that customers are moving beyond experimentation. NetApp logged roughly 500 AI and data-preparation wins in the quarter alone, with more than 1,100 for the full fiscal year.
Where the Growth Is Coming From
All-flash storage revenues climbed 18% year over year to $1.2 billion in the fourth quarter. Public cloud revenues rose 11% to $182 million. For the full fiscal year, all-flash hit $4.2 billion and public cloud reached $688 million.
Kurian said demand has been strongest where AI workloads require high-performance storage and data mobility. Keystone, the company's consumption-based buying model, grew about 65% in fiscal 2026 as customers shifted away from traditional purchasing.
NetApp also announced new products tied to AI deployments, including AI Data Engine and expanded collaboration with Google Cloud on distributed cloud offerings.
Fiscal 2027 Guidance Points to Acceleration, With a Margin Trade-Off
Chief financial officer Wissam Jabre guided for fiscal 2027 revenues of $7.33 billion to $7.58 billion, implying 8% growth at the midpoint. Non-GAAP earnings per share are expected to reach $8.70 to $9.00, representing 9% growth.
For the first quarter, NetApp expects revenues of $1.75 billion to $1.90 billion. That guidance includes an extra week worth approximately $65 million in revenue, mostly from support and cloud services.
The company projected non-GAAP gross margins of 68.5% to 69.5% for fiscal 2027, down from 71.3% in fiscal 2026. Management attributed the decline to memory and component costs but said pricing actions are underway to protect profitability.
Management Addresses Demand Sustainability and Margin Recovery
Analysts pressed management on whether all-flash demand was being inflated by customer pull-forwards ahead of price increases. Kurial said accelerated decision-making exists but characterized its impact on fourth-quarter results as minimal, attributing outperformance mainly to large deals discussed earlier in the year.
On margins, Jabre told analysts that product gross margin should reach a trough in the July quarter, with gradual improvement thereafter as pricing changes take effect. The company's long-term target remains in the mid-50% to high-50% range.
That exchange clarified the strategic trade-off: NetApp is leaning into demand opportunities while signaling that cost recovery will take multiple quarters rather than appear immediately.
AI Opportunity Spans Multiple Use Cases
When asked to quantify fiscal 2027 AI revenue, Kurial declined to provide a specific figure. Instead, he said the roughly 500 AI wins in the quarter covered on-premises deployments across data preparation, model training and inferencing use cases.
That detail matters. It shows NetApp's AI opportunity is not confined to a single workload and that the pipeline spans enterprise and cloud-native accounts.
Kurial also confirmed that newer offerings such as AFX have already generated wins in targeted verticals, while AI Data Engine is receiving positive customer feedback.
Capital Allocation Reflects Confidence
NetApp generated $900 million of free cash flow in the fourth quarter. The company returned $303 million to shareholders through dividends and buybacks and added $1 billion to its share repurchase authorization.
Kurial closed the call by positioning NetApp at the intersection of AI, cloud and data governance. Jabre emphasized disciplined execution around pricing, margins and cash flow.
For management teams evaluating storage and data infrastructure for AI projects, the earnings call underscores that enterprise adoption is moving beyond pilots. The margin pressure NetApp disclosed also signals that infrastructure costs will remain a consideration in AI deployment budgets. Learn more about AI for Executives & Strategy to understand how these infrastructure shifts affect organizational planning.
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