Digital Economy Dispatch #240 -- A Digital Transformation Perspective on the UK Spending Review 2025

It’s taken a while. But in the last few days, the UK government has released details of its spending review and priorities for the next few years. Although various details were contained in earlier funding announcements, this is the UK's first multi-year spending review since 2021 and sets the financial course for government departments. It determines their day-to-day budgets for the next three years, covering staff costs and public services, and also allocates investment funds through the end of the decade for new infrastructure projects such as hospitals, schools, and military equipment.

While it is a broad and complex document, in looking at the details I'm struck by what appears to be a watershed moment for the UK’s digital transformation ambitions. The government has placed AI and digital technology at the heart of its strategy, with £2 billion allocated specifically for AI development through 2029/30 and substantial investments across digital infrastructure, skills, and public service modernization. This re-affirms the UK’s determination to compete in the global AI race.

I’ll leave you to view the document and see the details. However, as you consider these impressive funding figures, I’d ask you to also ask an important question: How prepared are we to deliver responsible AI at scale at this magnitude and pace?

Key Themes: Sovereignty, Scale, and Service Transformation

Looking at the spending commitments, three dominant themes emerge. First is digital sovereignty, with the creation of a £500 million UK Sovereign AI Unit designed to reduce dependence on foreign AI capabilities. This reinforces a fundamental shift from previous approaches that relied heavily on international partnerships and private sector leadership. The £750 million Edinburgh supercomputer investment is an example of this sovereignty agenda, positioning the UK to compete with similar national AI infrastructure projects globally.

Second is the emphasis on scale, particularly evident in the commitment to expand the UK's AI Research Resource by at least 20-fold. This ambitious target suggests the government recognizes that incremental improvements will not suffice in the current AI landscape. The scale of investment across research and development, reaching £22.6 billion annually by 2029/30, positions the UK among the world's most aggressive public investors in emerging technologies.

Third is the integration of digital transformation across public services, with £10 billion earmarked for NHS technology modernization and £3.25 billion for the Transformation Fund to drive digital-first approaches across government. This represents a move beyond isolated pilot projects toward systematic digitization of public services and operations.

Driving Responsible AI Adoption

Focusing on the structural aspects of the review, I was pleased to see several positive indicators for responsible AI scaling. The establishment of the AI Security Institute with £240 million in funding demonstrates recognition that AI safety cannot be an afterthought to deployment. This proactive approach, combined with substantial investment in skills development through TechFirst (£160 million) and new AI courses, suggests to me an understanding that responsible AI adoption requires both technical safeguards and human capability development.

What is also encouraging is the emphasis on collaboration between universities and businesses in developing AI curricula, which indicates a commitment to embedding practical considerations into AI education from the ground up. The £48 million Tech Expert programme could help ensure that AI implementation across government supports business-led needs for AI literacy that combines responsible decision making with technical competence. Let’s hope that existing university-business partnerships can be strengthened to deliver on these goals.

Perhaps most significantly, we see that the integration of AI investment with existing public service modernization suggests a measured approach to deployment. Rather than treating AI as a separate technological layer, the review positions it as part of broader digital transformation efforts, potentially enabling better governance and accountability structures. Something I have been promoting for some time, and much needed given the stated challenges with today’s government infrastructure.

The £240 million Growth Mission Fund's focus on local economic development also suggests awareness that AI benefits must be distributed geographically, not concentrated in traditional tech hubs. This could help address one of the most significant risks of AI adoption: reinforcing existing regional inequalities.

Critical Gaps and Potential Risks

With AI and digital transformation a clear focus, attention must turn to delivery. Despite the substantial financial commitments, my concerns centre on where the spending review stops and the challenges of delivering AI at scale begin. Most troubling is the absence of dedicated funding for AI ethics oversight or algorithmic accountability frameworks. While the AI Security Institute addresses technical safety, is there sufficient attention to the broader societal implications of rapid AI scaling across public services? Recent concerns, such as a notable hesitancy in creating a UK AI Act, might suggest that accountability and regulation are now seen more as an inhibitor to the UK’s AI ambitions than a necessary balance to Big Tech’s market dominance.

From this perspective, the review's emphasis on speed and scale may conflict with responsible deployment principles. The commitment to "at least 20-fold expansion" of AI research resources could be seen as a quantity-over-quality approach that could overwhelm existing governance structures. Without corresponding investment in regulatory capacity and ethical oversight, I worry this rapid scaling risks deploying AI systems before adequate safeguards are established. It will be interesting to see how research priorities are established and the way the funding is disbursed to ensure that advancing “state of the art” is balanced with necessary investment to drive “state of the practice”.

In a similar way, the skills investment, while substantial, must not be too heavily weighted toward technical capabilities rather than the interdisciplinary expertise required for responsible deployment of AI and effective AI governance. My reading of the review is that there is an absence of specific funding for AI policy research, social impact assessment, or public engagement initiatives, which suggests a technology-first approach that may struggle to overcome complex ethical and social challenges. I hope that this is more my mis-reading than a lack of priority for these areas.

Additionally, it would have strengthened the review to see clearer mechanisms for public participation in AI development decisions. While democratic accountability is mentioned in general terms, there appear to be no specific provisions for citizen involvement in determining how AI should be deployed in public services affecting their daily lives. We must address fears that technologies dehumanize and that people feel that they are having AI and digital transformation "done to them".

On a personal note, the international dimension also presents a challenge to me. While the sovereignty agenda is politically appealing, it risks isolating the UK from important multilateral AI governance initiatives and could duplicate efforts rather than leveraging international cooperation on shared challenges. Explicit alignment (particularly with the US and EU) seems to be even more essential in these turbulent days.

International Context: Diverging Approaches

Having lived and worked in the US and Spain for many years, I can’t help but compare the UK approaches to AI and digital transformation to both US and European strategies. From my perspective, I see the United States continue to rely heavily on private sector innovation, with federal AI investment focused primarily on defence and research applications. The US national AI strategy approach is based on a more distributed style, emphasizing public-private partnerships rather than centralized government control.

In contrast, the European Union's AI Act represents what I see as the opposite extreme, viewing AI as “a human right” and prioritizing comprehensive regulation before widespread deployment. While this approach has faced criticism for potentially stifling innovation, it demonstrates greater attention to ethical considerations and citizen rights than is implied in the UK review.

In my view, the UK's approach appears to try to “split the difference”, emphasizing rapid scaling while acknowledging safety concerns. My worry is that this middle path risks achieving neither the speed of innovation of the US model nor the comprehensive safeguards of the European approach. The sovereignty emphasis also contrasts with the EU's focus on international standard-setting and the US reliance on market mechanisms. Without great care, the UK approach may backfire.

What to Do? Four Key Actions for Leaders

Based on my reading of this review and recent discussions with many organizations, digital leaders and decision-makers must view this spending review as both an opportunity and a warning. The substantial funding announced creates unprecedented possibilities for AI-enabled transformation and will undoubtedly drive the pace of AI adoption. However, the execution risks cannot be ignored and are equally significant. This suggests four key urgent actions for digital leaders.

First, this review reinforces the need for organizations to develop robust AI governance frameworks immediately, rather than waiting for government guidance. The review's emphasis on rapid deployment suggests to me that regulatory frameworks will struggle to keep pace with implementation. As a result, digital leaders and their organisations need to act now.

Second, I believe digitally mature organizations should prioritise interdisciplinary AI teams that combine technical expertise with business, ethical, legal, and social science perspectives. The review's skills focus on technical capabilities creates what I see as a market opportunity for broader AI literacy. It’s time to get everyone in your organisation moving up the AI maturity ladder.

Third, I encourage our digital leaders and their organisations to engage proactively with a wide set of stakeholders, local communities, users, and employees affected by AI deployments. This investment will increase pressure on leaders to act – and fast. Yet, the review's priorities also create increased reputational and leadership risks. Conversely, there are opportunities for organisations that encourage transparent, participatory approaches to responsibly adopt AI with agility.

Finally, I would suggest that digital leaders prepare for a difficult period of regulatory confusion in the AI landscape in which UK-developed capabilities diverge from international standards. This requires constant engagement with AI regulatory and policy organisations to stay informed. Leaders can increase flexibility by ensuring interoperability and data portability in AI system design.

Last Word

There is no doubt that the UK Spending Review 2025 represents the UK’s most ambitious commitment to AI leadership. It challenges digital leaders to drive their organisations with an accelerated AI strategy response.  In my view, the ultimate success of this spending review will depend on how digital leaders refine their AI execution strategy to balance innovation with responsible AI delivery. Those digital leaders who navigate this challenge effectively will help determine whether the UK emerges as a model for responsible AI scaling or a cautionary tale of technological overreach.