Tarek Nseir is co-founder of Valliance and a senior value partner, focused on delivering leading AI time-to-value for clients across Europe.
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Technology sovereignty has become a distraction in the ongoing conversation around how the UK can become the AI leader it aspires to be. Progress so far has been slow-going and if enterprises are to grasp the AI opportunity with both hands, they can’t have critical infrastructure held back by questions over where the builders are based.
Policymakers are overly focused on who controls critical systems, where they are built and whose values they reflect. These are valid concerns, but waiting for them to be addressed only risks setting businesses further behind competitors in the US and China at a crucial moment in the AI race.
The UK’s most consequential decisions on sovereignty were made decades ago. During the rise of cloud computing and large-scale software platforms in the '90s and early 2000s, the country chose integration over ownership. We can’t undo these decisions or let it slow down this next technological revolution.
This reality unveils the more immediate challenge afoot: the UK needs to focus on delivering outcomes for businesses with the right tech, now, rather than treating sovereignty as a prerequisite for progress.
Technology debates are too often framed around which companies should be trusted, rather than how systems should be governed. This framing is unhelpful and it actively slows progress for enterprises looking to actively scale AI in the UK.
The NHS’s work with Palantir is a perfect example of where independence is distracting from delivering outcomes. Addressing record wait times, uneven standards of care and deep structural inefficiencies require joined-up systems and unified patient data. The simple truth is that delivering this kind of infrastructure at scale is extraordinarily difficult, and only a very small number of organizations globally have the capability to do it. In practice, that has meant relying on providers like Palantir, not as a matter of ideology, but because the alternative is continued fragmentation and delay.
The government spends too much energy on scrutinizing where tech is built rather than establishing governance frameworks to operate responsibly with foreign firms. This sends the wrong message to businesses that—like the NHS—face structural challenges of their own and need guidance on how to address them.
The economic risk of delay is already becoming visible. By the government’s own admission, just one in six UK companies have adopted AI. Even within government, progress has been limited, with FOI disclosures highlighting how narrow early deployments have been, often restricted to basic tooling rather than meaningful transformation. For a technology that could double, even triple the UK’s GDP if scaled correctly, slow business adoption threatens to let local enterprises lag further behind.
With OpenAI halting its Stargate UK data center investment due to the nation’s "regulatory environment," we’re already seeing what happens when we’re not aligning with the world’s biggest AI firms. Local data centers would have been hugely valuable for businesses looking to use OpenAI’s models, as it would have allowed them to analyze and input personal data without breaching GDPR rules. Now they’re stuck with band-aid solutions.
More give-and-take is required for the public-sector to deliver what enterprises need to maximize AI’s value. For businesses, this only serves to make clear why collaboration with overseas AI firms will be crucial for unlocking truly transformative gains.
OpenAI, Microsoft, Google and Palantir sit at critical points in the value chain for scaling AI. Businesses need to trust what these companies can produce, even if they don’t agree with some of their other work.
Attempting to sidestep these platforms is unrealistic. Recreating equivalent capabilities locally would require enormous capital and long development cycles, and while that’s a worthwhile long-term ambition, enterprises cannot wait for those players to arrive.
A more pragmatic approach accepts current realities while focusing on control through governance. Working with global providers under clear regulatory frameworks that define data access, auditability, accountability and exit routes ensures that data is used responsibly, and businesses can unlock the value they seek from the right providers, with the right tech.
The UK shouldn’t be choosing between global technology providers or investing in domestic capability—both can happen at once.
Working with US AI providers must be done strategically, governed carefully and deployed with clear value in mind. This is where the private sector needs to be focused, and where the attitudes of policy makers must be moving towards.
The enterprises that benefit most from AI won’t be those that wait for ideal conditions, even if that’s the position of the authorities. They will be the businesses that act decisively, accepting the constraints that exist and continuing to innovate with AI anyway.
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