HPE Pulls 2028 Targets Into 2026 on AI Server Demand

Bloomberg showed Hewlett Packard Enterprise up 21.47% intraday after what it called a “blowout AI revenue forecast.” Caroline Hyde said the stock had reached a record high, made a record move, and added $13 billion in market value.

Antonio Neri said the quarter was “exceptional” across several key metrics, but his central claim was not simply that demand had spiked. He argued that demand is durable because HPE’s portfolio now sits at the intersection of networking, cloud, and AI, and because the company has both a “record breaking backlog” and a pipeline that remains “multiples of that backlog.”

That durability, Neri said, is why HPE raised its 2026 guide and issued a 2027 guide six months early. When Ed Ludlow separated two possible explanations for the outlook — more volume versus higher pricing — Neri said HPE is effectively pulling forward, into 2026, the 2028 outlook it had given at its securities analyst meeting the previous October.

Neri said that midpoint is “a dollar higher than the previous guidance.” His answer framed the revenue outlook as “a volume story with very disciplined pricing execution,” not simply a case of charging more for broadly similar server volumes.

Antonio Neri repeatedly returned to networking as the core of HPE’s improved financial profile. He said the company now has an $11 billion networking business, and that this changes the mix behind gross margin. HPE’s gross margin, he said, reached a record 36.9%.

The demand numbers he cited were broad across the portfolio. Campus and branch orders were up almost 30%. Data-center switching orders were up close to 20%. On the server side, Neri said demand was up triple digits. Storage had delivered triple-digit growth for the sixth consecutive quarter. HPE’s private-cloud portfolio, including what he called “AI factories for enterprise,” continued to grow.

The tension in the forecast is that HPE also faces rising component costs. Caroline Hyde noted that the company expected operating profit growth of 80% to 85% for the fiscal full year even as memory prices were “going through the roof.” Neri’s answer was that the portfolio mix and cost programs are offsetting those pressures. He pointed to the networking business’s contribution to gross margin and said HPE is ahead of plan on “Juniper and Catalyst initiatives,” both in milestones and synergies, which he said are improving cost of sales and operating expenses.

He did not dismiss memory inflation. He specifically named DRAM and NAND cost increases. But he treated them as subordinate to the demand environment. Customers, he said, “need access to this technology,” and demand is extending beyond build-out into enterprise adoption, especially AI inferencing.

Antonio Neri said HPE’s outlook was not transformed by a single customer. He described the company as having been selective in “AI at scale,” with attention to profitability and working capital, because those large-scale deployments require significant working capital.

That selectivity fits the balance-sheet priorities Neri described: paying down debt while driving profitable growth through networking, cloud, and AI in enterprise, sovereign, and inferencing use cases. His argument was that the enterprise AI opportunity is broader than a single hyperscaler-style order cycle.

Neri said many customers are bringing AI infrastructure on premise for compliance, governance, data privacy, and security reasons. He used HPE itself as the example: the company has 1,200 AI use cases internally, of which 250 are in production. Those deployments use a combination of proprietary closed models and open models, with what he called “very stringent governance,” and they run on premise.

The example was meant to support Neri’s broader claim that more enterprise customers are bringing infrastructure on premise when governance, compliance, privacy, or security requirements demand it.

Ed Ludlow drew a distinction between an enterprise “super cycle” and a deeper change in corporate spending driven by agentic AI. Antonio Neri chose the latter. His view was that agentic AI is changing business processes and workflows, making companies more agile and efficient, and that enterprise adoption remains early.

That answer placed HPE’s forecast inside a broader claim about corporate behavior. Neri said customers do not want to be left behind, and he tied that urgency to a phrase used inside HPE: “the future belongs to the fast.” He also connected the shift to lessons from Covid, when companies accelerated their digital adoption.

Neri’s thesis was that AI is ultimately about productivity. In that framing, HPE’s demand signals are not just evidence, in his telling, of a refresh cycle in servers and networking gear. They are evidence that companies are beginning to use AI to change how work gets done, which in turn supports demand for the infrastructure HPE sells.

Caroline Hyde pushed the productivity argument into its labor consequences: if AI improves productivity, does that mean fewer jobs or a different hiring model? Antonio Neri did not claim employment would be unaffected. He said the types of roles HPE hires for are “definitely” changing.

His answer focused on talent development rather than headcount reduction. He said HPE has an “aggressive” talent development and succession plan, and that he was scheduled to meet with his team on that subject later the same day. The larger point was that future skill sets have to evolve.

Neri said he reminds HPE’s 65,000 employees to use AI in their favor to become more productive. He extended that beyond technical staff, telling the Bloomberg anchors that “everyone,” including them, needs “a minor in AI.” In his view, the ability to use the technology will become a competitive advantage in every role across the enterprise.