Should HPE's Government AI and Supercomputing Partnerships Spark Strategic Moves From Hewlett Packard Enterprise (HPE) Investors?
In late October 2025, HPE announced major AI and supercomputing collaborations with the U.S. Department of Energy, Oak Ridge National Laboratory, Los Alamos National Laboratory, and a mix of enterprise and municipal clients. The focus: secure, high-performance, and sustainable infrastructure built for sovereign AI needs. For government leaders, this signals a credible partner for projects that require data control, compliance, and scaled compute.
Why this matters for government programs
- Data control and security: On-prem and hybrid AI stacks reduce exposure to uncontrolled data flows and help meet classification, locality, and audit needs.
- Mission delivery: AI supercomputing enables faster modeling, simulation, and analytics for science, defense, health, climate, and smart city operations.
- Sustainability: Next-gen systems are built with energy efficiency in mind-key for budgets, facilities planning, and emission targets.
- Procurement clarity: Multi-year, as-a-service models can align with appropriation cycles if SLAs and exit options are explicit upfront.
Investment narrative in plain terms
Owning HPE still means betting on a shift from traditional hardware to higher-margin, AI-centric and hybrid cloud offerings. The new government and research wins are meaningful, but they don't remove the core execution risk: growing software and services fast enough to offset lower-margin hardware exposure.
Near term, the key lever is scaling as-a-service revenue. Competitive pressure from public cloud providers and integration work tied to the Juniper acquisition continue to overhang sentiment.
The DOE "Mission" and "Vision" supercomputers: signal value
HPE's rollout of "Mission" and "Vision" for the Department of Energy underlines its intent to lead in sovereign AI infrastructure. The contract points to rising demand for secure, high-performance systems where data sensitivity, workload isolation, and compliance sit front and center. The big question for investors: how effectively HPE converts these deployments into recurring, profitable revenue streams.
For context on federal HPC priorities, see the Department of Energy's programs in advanced computing here.
What the growth path implies
HPE's narrative targets $44.4 billion in revenue and $2.7 billion in earnings by 2028. That assumes about 10.3% annual revenue growth and a $1.6 billion earnings lift from roughly $1.1 billion today.
To get there, HPE needs steady bookings from public sector AI and supercomputing, rising service attach rates, and disciplined delivery. Slippage in any of those areas would put the timeline at risk.
Valuation snapshot
A fair value estimate of $26.51 suggests roughly 13% upside versus the current share price referenced in this analysis. That upside leans on execution in as-a-service, clean integration of Juniper, and continued momentum in government AI wins.
Other perspectives
Independent community estimates place HPE's fair value in a wide range-roughly US$17.90 to US$34.64 per share as of November 2025. The spread reflects different views on how fast HPE can shift to recurring, higher-margin services while competing with public cloud alternatives.
What public sector leaders should ask HPE now
- Data sovereignty and isolation: Will deployments support air-gapped modes, on-prem model training, and clear data residency controls?
- Security and compliance: What certifications and controls are available for high-impact and classified workloads, and how are updates audited?
- Service model clarity: Are SLAs outcome-based with uptime, throughput, and support metrics tied to penalties and credits?
- TCO and energy: Request facility, cooling, and power baselines-plus efficiency roadmaps tied to your budget cycle.
- Portability: Ensure workload portability across on-prem and cloud targets to avoid lock-in.
- Pilots first: Start with a contained use case (e.g., model training for a specific dataset) with measurable milestones before scaling.
- Upskill the workforce: Pair deployments with practical AI training for program teams and operators. Curated options by job function are available here.
The bottom line
HPE is building a credible position in sovereign AI and supercomputing for government and research. The contracts matter, but the real test is conversion into durable, recurring profit.
For agencies and municipalities, HPE is worth a close look-provided contracts enforce data control, measurable outcomes, and clear exit ramps. For investors, this remains an execution story with upside if services scale on time.
This commentary is general in nature. It is not financial advice and does not consider your objectives or financial situation. It may not include the latest market-sensitive announcements.
Your membership also unlocks:
