Can the UK achieve the fastest AI adoption in the G7?

The Chancellor’s ambition for the United Kingdom to achieve the fastest adoption of artificial intelligence in the G7 is an important and welcome one. It signals recognition that AI is no longer a peripheral technological development but a central driver of productivity, competitiveness, and public service reform.

Yet the critical question is not whether this is an attractive ambition, but whether it is realistically achievable. The answer is yes, but only if AI adoption is understood as a broad-based process of economic diffusion rather than a narrow exercise in technological investment.

Too often, discussions of AI policy conflate invention with adoption. They assume that strong research performance, capital investment in frontier technologies, or national announcements on infrastructure are sufficient indicators of progress.

They are not. A country achieves rapid AI adoption when firms, public services, and institutions integrate AI into everyday operations, managerial processes, and decision systems at scale. Adoption, in other words, is less about isolated technological acquisition and more about the systematic embedding of capability across the economy.

On this point, the North of England is central to the national question. If the United Kingdom is to become the fastest AI adopter in the G7, this will not be achieved through London and the South East alone. It will depend upon whether the country can diffuse AI effectively across its full economic geography, particularly in regions with strong industrial capabilities but persistent barriers to innovation uptake.

The North possesses considerable assets in advanced manufacturing, energy, health, logistics and digital industries. However, it also faces well-established challenges in productivity, technology diffusion, skills formation and investment. These are not secondary concerns. They are decisive conditions for AI adoption.

Our recent work with the Northern Powerhouse Partnership argues that the long-standing productivity challenge in the North is not simply a matter of insufficient invention. It is also a matter of weak diffusion, uneven innovation capacity and constrained absorptive capability.

This distinction matters. AI will not improve economic performance merely because advanced tools exist. It will do so only where organisations can recognise their value, adapt them to local needs, redesign processes around them, and sustain their use over time. Without that capability, adoption remains superficial, fragmented and uneven.

This is where the policy debate needs greater precision. If the Government wishes to make the United Kingdom the fastest AI adopter in the G7, it must move beyond a frontier-only approach and adopt a wider diffusion strategy.

That means placing equal emphasis on the adoption capacities of firms, especially SMEs and mid-sized businesses, rather than focusing exclusively on high-profile technological breakthroughs. It means investing not only in computing infrastructure and leading research, but also in managerial capability, workforce skills, organisational redesign and regional institutional support.

Our own research in Durham University Business School on process innovation reinforces this point. New technologies generate value when they are embedded within core and enabling organisational processes, not when they are simply acquired as standalone tools. The successful use of external expertise is particularly important here.

Organisations often develop stronger innovation outcomes when they work with external partners who provide not merely technical solutions, but learning, adaptation and longer-term capability development. In the context of AI, this suggests that adoption will depend heavily upon ecosystems of collaboration involving universities, businesses, catapults, public agencies and intermediary institutions. The issue is not simply whether firms can buy AI, but whether they can learn how to use it well.

So, can the UK achieve the fastest AI adoption in the G7? It can, but only if it addresses four conditions.

1. First, AI diffusion must be treated as a national productivity priority. The objective should not be limited to developing world-class AI research or attracting large-scale investment at the frontier. It should also include helping firms across sectors and regions to apply AI in practical, commercially relevant ways.
2. Second, the Government must strengthen absorptive capacity. This includes technical competence, leadership capability, management quality and workforce readiness. Without these, AI tools will be underused, misapplied, or confined to isolated pilots with limited economic effect.
3. Third, policy must be explicitly place-based. A credible national strategy for AI adoption requires serious attention to the regions where the productivity gains from adoption could be substantial, but where barriers to implementation remain significant. The North is therefore not simply a beneficiary of AI policy, it is a test of whether that policy is serious.
4. Fourth, partnership institutions matter. Effective AI adoption requires trusted mechanisms through which firms can experiment, collaborate and de-risk implementation. This points to the importance of universities, innovation intermediaries, catapults and regionally embedded networks that can translate knowledge into application.

The Chancellor’s ambition is therefore achievable, but not automatically so. It will require a shift in emphasis from technological aspiration to institutional execution. The United Kingdom has the scientific base, the industrial capability and the regional assets to lead the G7 in AI adoption. What it now needs is a policy framework that understands adoption as a process of diffusion, learning and capability-building across the whole economy.

If that framework is put in place, the United Kingdom can move beyond rhetoric and become a genuine leader in AI adoption. If it is not, the ambition will remain impressive in tone but limited in effect.

More information

• This article is republished from The Northern Agenda Newsletter. Read the original article. 
• Professor Kieran Fernandes is Executive Dean of our Business School.
• Durham University Business School is triple accredited and ranked in the world top 100 for the Financial Times European Business School Ranking 2025. It is ranked 9th globally in the Financial Times Online MBA Ranking 2026 and joint 85th in the World for Financial Times Global MBA Ranking 2026. Visit our Business School webpages for more information on our undergraduate, postgraduate, MBA, DBA, Executive Education and PhD programmes.