HPE trims outlook on AI server delays: what sales teams should do now
Hewlett Packard Enterprise lowered its Q1 2026 revenue guidance to $9.0-$9.4 billion, below the $9.9 billion analysts expected. Shares dropped more than 3% at the open as buyers paused or pushed AI server deals into the back half of the year.
Management flagged volatile AI demand and later delivery timelines, with some large customers delaying orders. That drag showed up in the latest quarter: server revenue fell 5% to $4.5 billion, hybrid cloud was down 12% to $1.41 billion, and total revenue landed at $9.68 billion versus $9.94 billion consensus. A slowdown in U.S. federal spending added pressure.
Even with the softer top line, HPE raised its adjusted EPS outlook for FY 2026 to $2.25-$2.45 (from $2.20-$2.40), betting on an H2 rebound in AI server sales to support profitability.
Key numbers at a glance
- Q1 2026 revenue guidance: $9.0-$9.4B vs. $9.9B expected
- Stock reaction: down >3% at the open
- Servers: $4.5B, down 5%
- Hybrid cloud: $1.41B, down 12%
- Total quarterly revenue: $9.68B vs. $9.94B consensus
- FY 2026 adjusted EPS: $2.25-$2.45 (raised)
Why this matters for sales
- Timing risk: Big AI hardware deals are sliding into H2. Expect longer sales cycles and tighter scrutiny on delivery dates.
- Budget shifts: Some buyers will move spend from hardware to software, services, or pilots until hardware is available.
- Federal softness: If you sell into public sector, build in more approval steps and longer procurement windows.
- Proof beats promises: Buyers want clear deployment plans, realistic timelines, and measurable outcomes before committing.
Action plan for the next 90 days
- Reforecast by fulfillment date, not just close date. Tie each opportunity to ship/installation milestones.
- Offer phased rollouts (pilot → limited production → full scale). Reduce initial hardware ask and expand as capacity frees up.
- Bundle value now, capacity later. Lead with software enablement, MLOps setup, and data readiness while hardware queues clear.
- Put SLAs and acceptance criteria in writing. Align stakeholders on what "delivered" means to avoid rework.
- Lock pricing windows. Use time-bound quotes and renewal options to keep deals warm without constant repricing.
- Surface risk early. Add a delivery-risk field in your CRM and update weekly so leadership can protect forecast accuracy.
Messaging you can use
- "We'll start outcomes now-data pipelines, model packaging, and governance-so your hardware goes productive on day one."
- "If you prefer to stage capacity, we can schedule a phased deployment across quarters to match your budget and delivery timing."
- "We'll document milestones, test plans, and acceptance criteria up front to keep approvals fast and predictable."
- "We'll protect TCO through optimization and right-sizing so you don't overbuy to hedge delivery risk."
If you sell with or against HPE
- Co-sell: Set joint timelines, assign one owner for delivery communication, and share a single status update with the customer.
- Compete: Differentiate on deployment speed, services-led outcomes, flexible contracting, and clear rollout schedules.
- Renewals: For existing accounts, use interim value (optimization, governance, training) to de-risk churn while hardware lands.
What to tell leadership
- Flag any H1 AI hardware deals with shift risk and list what it takes to keep them in-quarter (financing, phased scope, services-led start).
- Shift enablement resources to pilots, MLOps, and data work that can close now and expand later.
- Track pushouts by sector (enterprise, federal, mid-market) to adjust territory focus and quota relief requests.
For the official updates and future guidance, check the HPE investor relations page.
If you want quick, practical training to strengthen your AI sales conversations and value framing, explore courses by job at Complete AI Training.
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