HPE Private Cloud AI and the case for sovereign AI
Why are more UK organisations moving production AI off public cloud, and onto infrastructure they can control?
The Softcat News Team
AI is now the workload that forces the data question. Deloitte reports that 83 per cent of enterprises treat sovereign AI as important to strategic planning, and the reason is rarely cost alone. Control has become the real constraint.
Sovereignty has moved from preference to requirement
AI has moved from pilots to production across the most data-sensitive parts of the economy. In financial services, the Bank of England and the Financial Conduct Authority found that 75 percent of UK firms now use AI. Healthcare, government, defence and research are on the same path. What they share is data they cannot afford to expose.
That data sits under rules that the public cloud cannot easily satisfy. Patient records, citizen data, classified material, genomics and unpublished research each carry their own controls. Move it into a shared public tenancy, and you raise questions of jurisdiction, access and accountability.
Cost is the other half of the case. Public cloud suits experimentation, but production AI runs constantly, turning metered GPUs and data egress into an unpredictable bill. Owning the platform turns that into a fixed line.
Regulation across the UK is moving in the same way. The UK government introduced the Cyber Security and Resilience Bill in November 2025, widening its scope to data centres and critical suppliers. Deloitte found that 77 percent of organisations now consider an AI system’s country of origin when selecting a vendor. Sovereign capacity is shifting from differentiator to baseline.
The platform arrives built, not assembled
HPE Private Cloud AI is, in plain terms, a private cloud built for AI. It is co-engineered by HPE and NVIDIA and arrives as one working system. Compute, storage, networking and AI software are pre-integrated and validated together, so interoperability is never your responsibility to engineer or maintain. The integration risk that sinks DIY AI stacks is gone.
Your team does not spend weeks wiring it up. Instead, the platform moves from concept to production within a matter of days, with models ready from a curated catalogue. For the most sensitive workloads, an air-gapped option keeps them fully isolated, which is the whole point in regulated work.
Security and data residency are built into the design, not bolted on afterwards. You can buy the platform outright or consume it via HPE GreenLake, matching the commercial model to how the work is funded. Full configuration and sizing details are in HPE’s published specifications for the teams who need them.
The result is refreshingly simple: a private cloud for AI that is ready to work, not a project to assemble.
Where specialist partner changes the outcome
Choosing the platform is one decision, but what surrounds it decides the outcome. This is exactly where breadth matters.
Softcat advises across on-premises, public and multi-cloud before any product decision; the answer starts from the workload. Our specialists span data, AI, infrastructure, security and procurement. We carry the business case, the design and the build, removing the handoffs where AI projects usually stall. Few resellers can cover that full span of work.
Our data and AI practice do the thinking before the buying. We map the highest-value workloads, test them on the right platform and build the business case that unlocks funding. These are infrastructure choices then follow the use case, not the other way around.
Real scale sits behind that advice, with Softcat working across the full HPE enterprise portfolio for thousands of customers. It is shaped by what works, not by what is in stock. For a regulated estate, that independence matters as much as the technology.
HPE’s recognition backs this up too. We hold HPE Platinum Partner status, alongside HPE International Solution Provider status. HPE named Softcat Global AI Partner of the Year and UKIMEA Solution Provider Partner of the Year 2026, as well as UKIMEA AI Partner of the Year in 2025.
The decision shapes the next three years
The choice for IT leaders is not really about models. It is about where production AI runs, who controls the data, and how predictable the cost becomes. Refresh decisions made now will shape capability for years. For regulated, sensitive or sovereignty-bound work, the centre of gravity has already moved.
Whether you are scoping a first production workload or consolidating AI infrastructure across the organisation, the right partner decides the outcome. Speak to one our specialists to get the conversation started for your organisation.