HPE's AI server sales slip on customer delays - what sales teams should do next
Hewlett Packard Enterprise beat earnings but missed revenue as AI server shipments got pushed out. EPS came in at 62 cents vs. 58 cents expected, while revenue landed at $9.68 billion against $9.93 billion estimates.
Server revenue - the recent growth engine - fell 5% to $4.46 billion, with operating margin down to 9.8% from 11.6% a year ago. HPE still booked an extra $2 billion in AI server orders, but some large customers weren't ready to receive shipments.
Leadership pointed to more government and big-enterprise deals, which come with slower procurement, detailed acceptance criteria, and export-control hurdles. "You'll see a lot more of that with AI," said the finance chief. "It tends to be a lot more lumpy." For context on export rules affecting AI chips, see the U.S. Bureau of Industry and Security's updates here.
HPE also emphasized its pivot toward networking after closing the $14 billion Juniper deal. Networking revenue jumped 150% to $2.8 billion, with a shift to higher-value products and better margins. "We are now at the core a networking-centric company," said the CEO.
Elsewhere, hybrid cloud dropped 12% to $1.4 billion and financial services was roughly flat at $889 million. For the current quarter, HPE guided revenue to $9.0-$9.4 billion (below the Street's $9.88 billion) and EPS to 57-61 cents (above 53 cents expected).
Full-year guidance holds. The company raised its annual adjusted EPS outlook to $2.25-$2.45, up from $2.20-$2.40. Management expects a stronger second half of fiscal 2026 as Juniper synergies increase and component costs (like memory) potentially ease.
Investors weren't thrilled. The stock fell more than 9% after hours, trimming a year-to-date gain of just over 7% - shy of the S&P 500's move this year.
What this means for sales teams
- Enterprise AI deals carry readiness risk. Add delivery-readiness checkpoints (facilities, data pipelines, security, acceptance criteria) to your close plan to avoid last-minute shipment pushes.
- Structure contracts for reality. Use phased shipments, bill-on-acceptance milestones, and explicit acceptance testing to align revenue, cash, and deployment timelines.
- De-risk export and supply constraints early. Include an export-compliance plan, alternate SKUs, and lead-time ranges on AI accelerators and memory to keep options open.
- Lean into networking now. With HPE calling itself networking-centric, lead with fabric upgrades, AI-ready switching, and secure segmentation - often faster cycles than compute refreshes.
- Bundle outcomes, not boxes. Tie AI servers to networking, storage, and ops automation with a clear TCO and time-to-productive-use story. Large buyers want fewer vendors and accountable timelines.
- Forecast with "lumpiness" in mind. Weight big-government and global enterprise deals lower until readiness gates are confirmed. Track slip causes by stage and act on the patterns.
Talk tracks you can use this week
- "Let's lock a deployment checklist with facility, data readiness, and model ops milestones so delivery matches when you can plug in and go live."
- "We can phase shipments: core networking first to prep the fabric, then servers as soon as your data and governance are cleared."
- "Given export-review timelines, we'll include a compliant alternate configuration so your schedule doesn't stall."
- "Here's a bill-on-acceptance structure tied to your internal testing window - you only pay once your team signs off."
Forecast hygiene and deal mechanics
- Define stage exit criteria around customer readiness (PO issued, site complete, data governance approved, export checks passed, acceptance plan signed).
- Measure acceptance-to-ship cycle time and slip ratio by segment; review weekly with delivery and finance.
- Set executive anchors on the largest opportunities: executive sponsor named, deployment owner assigned, compliance owner engaged.
- Where possible, attach a networking "prep" deal ahead of server delivery to create progress, revenue, and customer momentum.
If you or your team need sharper AI solution-selling skills - from buyer education to deployment planning - explore role-based programs at Complete AI Training.
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