The UK and Australia are deepening cooperation on artificial intelligence (AI) security, with a new agreement designed to help both countries respond to fast-moving risks from powerful AI systems.

The Memorandum of Understanding (MoU), announced as ministers meet in Canberra, will bring together the UK AI Security Institute and the Australian AI Safety Institute. The partnership will focus on frontier AI capabilities, including how advanced systems could be used in cyber-attacks, as well as how AI could strengthen cyber defence.

The agreement comes at a time when governments are increasingly concerned about the speed at which AI systems are developing. While AI is expected to support economic growth, improve public services and strengthen national capability, ministers are also warning that the same technology could be used to scale cyber threats, automate malicious activity or accelerate the discovery of new vulnerabilities.

Under the new partnership, the two institutes will share information on AI capabilities, collaborate on research into emerging risks and work together on international best practice for testing and evaluating AI systems. The agreement will also allow for staff exchanges between the two institutes, building day-to-day cooperation between teams working on AI safety and security.

Ministers seek to stay ahead of fast-moving risks

UK AI Minister, Kanishka Narayan signed the agreement alongside Australia’s Assistant Minister for Science, Technology and the Digital Economy, Dr Andrew Charlton, in Canberra.

Narayan said the UK and Australia had “always worked closely” to protect their citizens, adding that the partnership “matters more than ever in the age of AI”. He warned that the technology is moving quickly, particularly in areas such as cyber security, and said: “No country can tackle that alone.”

His comments reflect a growing international consensus that AI safety and security cannot be managed by individual countries acting alone. As frontier models become more capable, governments are seeking to develop shared approaches to evaluation, risk monitoring and technical testing.

The UK has placed significant emphasis on AI safety since hosting the first global AI Safety Summit at Bletchley Park in 2023. The AI Security Institute has since become a central part of the UK’s approach to understanding the risks posed by advanced AI systems and informing policy decisions.

The new agreement with Australia adds another layer to that international work, strengthening bilateral cooperation with a close ally while contributing to wider efforts to build common standards for frontier AI assessment.

Frontier AI and the cyber security challenge

The Government said the agreement is being driven partly by new research from the UK AI Security Institute, which indicates that advanced AI systems are improving rapidly in their ability to carry out complex cyber-attacks. That creates risks for businesses, critical infrastructure and the wider public, but it also opens up opportunities for defenders to use AI to identify vulnerabilities, detect attacks and strengthen resilience.

This dual-use challenge is one of the central questions facing policymakers. The same capabilities that could help a security team analyse code, monitor threats or respond more quickly to incidents could also be misused by malicious actors to automate parts of the cyber-attack chain.

The UK and Australia’s approach appears to be based on the view that technical cooperation is essential. Rather than treating AI security as a purely domestic policy issue, the two countries will work together on testing, evaluation and research, helping to ensure that both governments have a stronger evidence base as the technology develops.

“This is exactly the kind of international cooperation we need to see more of. The UK has already established itself as a leader in AI security, and by working closely with trusted partners like Australia we can build the coalitions needed to stay ahead of fast-moving risks while ensuring AI is developed safely and responsibly.”

Tim Flagg, CEO, UKAI

Building international best practice

The partnership will also support work on international best practice for AI evaluation. That is likely to become increasingly important as governments, companies and research bodies seek clearer ways to assess whether powerful AI systems behave as intended.

The Australian Department of Industry, Science and Resources said MOU will provide a framework for technical cooperation and promote the safe and responsible use of artificial intelligence. It said the agreement would help both countries share expertise on emerging AI capabilities and risks, conduct joint research, and support international work on AI measurement, evaluation and science. The department added that the partnership would help both countries “keep pace with change” while ensuring communities share in the benefits of AI.

The UK AI Security Institute already works with research bodies across major economies through the International Network for Advanced AI Measurement, Evaluation and Science, as well as through bilateral partnerships. The Australia agreement adds to that growing network of cooperation.

AI security enters a new phase

The UK-Australia pact signals a shift in how allied governments are approaching AI risk. The pact demonstrates how governments are looking to move away from high-level principles or broad ethical statements. Increasingly, governments are moving towards practical technical cooperation: sharing research, testing models, evaluating capabilities and building institutional links between AI safety and security bodies.

That reflects the pace of change in the technology itself. As AI systems become more capable, the risks they pose are becoming more operational, particularly in cyber security. The challenge for governments is to keep pace without slowing the benefits AI can bring to innovation, economic growth and public services.

The agreement between the UK and Australia is therefore both a security measure and a strategic partnership. It aims to ensure that two close allies can better understand emerging AI risks, strengthen their defences and help shape the international standards that will guide frontier AI development in the years ahead.

Tim Flagg

Chief Executive, UKAI

The UK does not lack ambition on AI writes CEO of UKAI, Tim Flagg. What it lacks is the confidence and coordination to turn that ambition into delivery. This opinion article was written in response to the Get Britain Growing: South East conference sprint on AI.

Artificial intelligence is already shaping how organisations operate, how decisions are made, and how people interact with work, education, and public services.

Across the economy, AI is now foundational. It is changing the nature of productivity, transforming professional roles, and redefining the skills people need to participate in the modern labour market. As demonstrated at the AI sprint session of the Get Britain Growing conference in Brighton, for regions such as the South East, this presents an enormous opportunity. With world-class universities, innovative businesses and strong entrepreneurial networks, the region has many of the ingredients required to lead.

But potential is not the same as delivery.

The Gap Between Ambition and Adoption

In my role as Chief Executive of UKAI, I regularly speak with businesses, policymakers, educators, and technologists across the country. The message I hear again and again is strikingly consistent – the UK does not lack ideas about AI. What it lacks is coherence, confidence, and a clear route from ambition to implementation.

That is the challenge this Sprint on AI and Skills was designed to confront.

The South East is often presented as a single prosperous region, closely tied to London, and assumed to be well placed to benefit from the next wave of technological change. Yet that broad characterisation hides a more complex reality. Research excellence and technology firms sit alongside small and medium-sized businesses experimenting without support, communities facing limited access to opportunity, and public institutions struggling to keep pace with change.

This matters because AI adoption will not succeed if it is only concentrated in already advanced organisations. It must become something that businesses, public services, educators, and communities can understand, trust, and use effectively.

One of the strongest messages from the Sprint participants was that of frustration. Participants recognised the strength of the ideas in the room, but also the familiar risk that good conversations do not always translate into action. Too often, momentum fades once an event ends. Responsibility becomes unclear. Investment remains uncertain. The same problems are discussed again months later.

AI adoption cannot rely on enthusiasm alone. It requires structure, leadership, and accountability.

That is why the idea of a place-based approach is so important. Sussex offers a credible starting point; it is a region with strong socio-economic assets, the infrastructure, clear challenges, and institutions capable of convening across sectors. Local authorities, universities, employers, and community organisations all have a role to play. The question is whether those efforts can be aligned into a shared plan.

From Literacy to Regional Leadership

A core part of that plan must be AI literacy.

Many people are now using AI tools every day, but far fewer are using them well. Too often, AI is treated as a shortcut – a way to draft text faster, search for information or automate simple tasks. That underestimates its value and increases its risks. Used properly, AI can support analysis, decision making, service redesign, and organisational learning. Used poorly, it can reinforce mistakes, weaken trust, and create fear.

At UKAI we have highlighted how AI literacy is not simply a technical skill. It is a leadership capability. It requires judgement, ethical awareness, and confidence. Leaders need to understand where AI adds value, where it introduces risk and how humans remain in control. Without that understanding, organisations will either move too slowly or adopt tools without the right safeguards.

Education and skills reform must therefore sit at the centre of the regional growth agenda. We cannot prepare people for an AI enabled economy through systems that move too slowly to keep up with technological change. Graduates should not require extensive retraining before they are productive. Adults should not be locked out of reskilling because learning pathways are too rigid. Businesses should not struggle to find the talent they need while education providers work to outdated assumptions.

The answer is not to narrow education to technical training alone. In an AI driven world, human capabilities become more valuable, not less. Critical thinking, communication, creativity, collaboration, and ethical judgement are not optional extras. They are the skills that will determine whether AI strengthens or weakens our economy and society.

The prize is significant. The regions that succeed in the age of AI will not only be those that build the most advanced technologies. They will be the regions that adapt fastest – embedding AI into workplaces, public services and education systems in ways that enhance human capability.

As we discovered, the South East has the assets to lead. Sussex could become the testbed for a model of responsible, inclusive, and practical AI adoption that can be scaled nationally.

But that will only happen if we move from insight to implementation. The task now is to build the coalition with the new Mayoral Combined Authority, set the standards, invest in skills, and create the confidence required for AI to deliver real regional growth.

Find out more

To find out more about the 2026 Chamber UK Get Britain Growing Conference, please either visit www.chamberuk.com/events or for partnership opportunities, please contact ben.mcdermott@chamberuk.com. This conference is organised in partnership with Silverstone Communications.

To find out more about UKAI: click here.

The Get Britain Growing Conference was sponsored by HP. Find out more: click here.

A new Curia and UKAI report argues that Sussex can become a testbed for responsible AI growth – but only if skills, trust, leadership, and delivery are treated as regional infrastructure.

Setting out how Sussex could become a regional testbed for responsible artificial intelligence adoption, the report argues that the area has the assets to lead but lacks the coordinated delivery model needed to turn ambition into economic growth.

AI and Skills – Building Capability for Regional Growth, produced as part of the Get Britain Growing Report Sprint Three, follows a conference at the University of Sussex which brought together industry, academia, and government to explore how the South East can stimulate and sustain growth. The report focuses on the third sprint, which examined the skills, structures, confidence, and governance needed to harness AI for public value and regional economic development.

From AI ambition to delivery

The central argument of the report is that the South East does not lack innovation, ideas, or institutional assets. It has universities, businesses, investment networks, and public sector bodies that could support AI adoption at scale. The problem is that these assets are not yet sufficiently aligned.

As the report puts it, the region’s strengths “are not yet translating into coordinated AI adoption at scale.” It warns that adoption remains “uneven, risk-averse, and poorly supported by existing skills and education systems,” with fragmented initiatives and limited accountability holding back progress.

“The outputs of this Sprint offer a credible foundation for regional AI leadership that can be tested locally and scaled nationally” Tim Flagg, Chief Executive, UKAI

This is where Sussex becomes important. Rather than attempting to solve the entire South East’s AI challenge at once, the report proposes Sussex as a practical starting point: a place-based testbed where councils, universities, businesses, and communities can develop, test and refine a coordinated model.

AI literacy as a leadership capability

One of the strongest themes in the report is the need to redefine AI literacy. The discussion does not treat AI skills as simply a matter for coders, data scientists, or technology teams. Instead, the report argues that AI literacy must become a core leadership and civic capability.

Many organisations already use AI tools, but the report suggests that use is often shallow. AI is too often treated as a shortcut, search engine or writing aid, rather than as a tool for analysis, decision support, and organisational learning.

“Many people are using AI tools daily, but few are using them well” Sprint participant

This matters because low AI fluency affects procurement, governance, workforce planning, and public trust. Senior leaders who do not understand AI’s capabilities and limitations are less able to make confident decisions about adoption. In particular, public sector organisations may default to caution, informal bans or highly restrictive policies because they fear reputational, ethical, or operational risk.

The report therefore calls for mandated practical AI literacy programmes for councillors, senior officers, education leaders, and commissioners. It also recommends a Sussex-wide AI literacy framework, defining baseline literacy, advanced fluency, and leadership capability.

Education must move faster

The report is equally direct about the education and skills system. It argues that current models are too slow for the pace of AI-driven change, with long qualification cycles, rigid accreditation processes and weak links between education and industry.

Graduates, the report notes, are often not work-ready, while adults who need to retrain struggle to access flexible learning pathways. In response, it calls for more agile skills provision, including micro-credentials, bootcamps, stackable learning and industry-shaped curricula.

“Education and skills systems are structurally misaligned with the pace of AI change” Peter Swallow MP, Member of Parliament for Bracknell and member of the Education Select Committee

Member of Parliament for Bracknell and a member of the Education Select Committee, Peter Swallow MP makes the broader case in the report that AI does not reduce the importance of education. Instead, he argues that it changes what education is for.

“AI does not signal the end of education, but it challenges us to return to its core purpose – preparing people not for a single job, but for continuous personal and professional development.”

That framing is important. Unlike several AI and education/skills reports, the Curia and UKAI report does not argue for a narrow technical curriculum. Instead, it places problem-solving, communication, critical thinking, ethics, and adaptability alongside technical competence.

The Sussex AI Coalition

The report’s main delivery proposal is the creation of a Sussex AI Coalition. This would bring together local authorities, universities, employers, small and medium-sized enterprises, community organisations, and UKAI to coordinate activity across the region.

The coalition would be supported by a shared Sussex AI Manifesto, setting out principles for responsible and inclusive adoption. The report also proposes appointing a Regional AI Lead or Chief AI Officer equivalent to coordinate delivery and own the regional AI action plan.

The proposed implementation plan is built around four delivery pillars: governance and leadership; AI literacy and leadership capability; education, skills, and workforce alignment; and shared infrastructure, trust, and inclusion.

This structure is important because it moves the debate beyond general support for innovation. It gives the region a delivery architecture – who should convene, what should be built, what should be measured and how quickly progress should happen.

Shared infrastructure and inclusion

A further recommendation is the development of shared AI infrastructure, including a proposed Sussex GPT. The report describes this as a regional knowledge and literacy hub, designed to support policy, best practice and AI learning in a way that reflects local needs.

The report also stresses that infrastructure should not only mean technology. It should include data, standards, training, coordination, and ethical assurance. Shared infrastructure could lower barriers for SMEs, social enterprises, and public bodies, helping organisations that may not have the capacity to build AI capability alone.

“AI adoption risks deepening existing inequalities if inclusion is not designed in from the outset.” Peter Swallow MP

Inclusion is a recurring concern. The report warns that AI could deepen existing inequalities if digital exclusion is not addressed. Barriers such as poor connectivity, limited access to devices and lack of confidence could prevent communities from benefiting from AI-enabled education, employment, and public services.

Analysis: the report’s strength is its focus on delivery

The strongest part of the report is its insistence that AI adoption is primarily not a technology problem. It is a coordination problem across various economic sectors, and across government. The report identifies the familiar pattern of strong discussions, promising ideas, and limited follow-through. By focusing on ownership, governance, and delivery, it moves the debate from aspiration to implementation.

The Sussex model is also sensible. Regional AI strategies can become too broad to act on, while individual institutional projects can remain too small to scale. Sussex offers a middle ground – large enough to bring together councils, universities, employers, and communities, but focused enough to test what works.

However, the report’s success will depend on whether the proposed coalition has real authority, resources, and accountability. A manifesto alone will not change behaviour. As with other Mayoral Combined Authority regions, a Regional AI Lead could make a difference, but only if the role has the backing of local government, employers, and education providers.

The report is right to place AI literacy at the centre of the agenda. Without confidence and understanding, adoption will either be too slow or too careless. The real opportunity is not just to train more technical specialists, but to build an AI-capable civic and business culture across the region.

Ultimately, the report argues that Sussex should not simply adopt AI. It should demonstrate how AI can be embedded responsibly into education, work, and public life. If that can be delivered, the region could offer a practical model for AI-enabled growth that other parts of the UK can learn from.

Find out more

To find out more about the 2026 Chamber UK Get Britain Growing Conference, please either visit www.chamberuk.com/events or for partnership opportunities, please contact ben.mcdermott@chamberuk.com. This conference is organised in partnership with Silverstone Communications.

To find out more about UKAI: click here.

The Get Britain Growing Conference was sponsored by HP. Find out more: click here.

Adama Ibrahim

UKAI Life Sciences Working Group (Panel Chair)

Following the publication of the Curia and UKAI AI Is Ready. Is the System? report, Adama argues the UK’s problem is not AI innovation but delivery – fragmented healthcare systems and slow adoption are the real barriers. She calls for aligned infrastructure, regulation, and culture to move from pilots to scalable impact in healthcare. (Photo: UKAI Life Sciences Working Group member, Adama Ibrahim chaired the Parliamentary session, kindly hosted by Shadow Equalities Minister, Mims Davies MP.)

When we convened these discussions in Parliament to help produce the AI Is Ready. Is the System? report, the objective was to move the conversation from pilots to scalable infrastructure, from policy statements to practical delivery.

The UK has not lacked ambition since the publication of the Government’s AI Opportunities Action Plan. We have committed to AI at scale and articulated a vision for research excellence and preventative healthcare. We have world-class scientists, innovative companies, and a health system rich in data. But ambition alone does not deliver outcomes. The pathway from strategy to routine clinical practice is complex – and, at times, uncomfortable.

AI does not simply automate existing systems. It exposes their imperfections.

Throughout these sessions, we heard repeatedly that the barriers to scale are not rooted in a lack of technology. They lie in fragmented governance, legacy infrastructure, unclear ownership, and cultural hesitation. In secondary care, clinicians face multiple logins and siloed data. In primary care, digital maturity varies by locality. Startups encounter data access processes that outlast their funding cycles. Boards hesitate because liability is not always clearly defined.

None of these issues are insurmountable, but they require coordinated leadership.

The Real Barrier: From AI Innovation to Healthcare Implementation

One of the strongest messages from industry during the course of this programme was that deployment, not invention, is the bottleneck. Even if no new AI tools were built from tomorrow, it would take years to embed what already exists. That should focus our attention. This means that by the time they are deployed, they may largely become out of date. Measurement, evidence generation, and clear pilot exit criteria are essential. Trust is built through lived experience in real clinical settings, not through PowerPoint presentations.

At the same time, the global environment is moving rapidly. International markets are experimenting with direct-to-patient AI-enabled tools. Investment is flowing toward jurisdictions that provide clarity, interoperability, and predictable regulation. If the UK allows caution to become delay, we risk losing not only economic advantage but also the opportunity to shape standards aligned with our values of fairness, transparency, and safety.

Prevention illustrates the scale of the prize. Genomic risk scoring and predictive analytics can identify vulnerability years before disease manifests. Yet prevention is still funded from the same constrained budgets as acute care. If we are serious about shifting from reactive to preventative medicine, our funding and evaluation models must reflect that intent.

Trust must also remain central. Concerns about bias and representation are legitimate. AI systems learn from data, and if that data fails to reflect the diversity of our population, outcomes will differ. Transparency in training data, subgroup performance monitoring, and meaningful public engagement are not optional extras – they are foundational to confidence.

From Insight to Action

Within the UKAI Life Sciences Working Group, our role is to bridge sectors. We bring together small and medium-sized businesses (SMEs), established industry, clinicians, and policymakers to ensure that solutions are co-designed and grounded in real need. Collaboration must replace transaction. Safety case methodology must evolve with adaptive AI. Infrastructure must be treated as a national asset, not a discretionary upgrade.

Above all, culture matters. Fear based environments do not innovate. Curiosity, openness, and shared learning accelerate adoption. We must normalise iterative improvement rather than demanding perfection before first deployment.

This report does not represent the end of a conversation. It marks the beginning of a more coordinated phase of work over the course of the year ahead. The challenge is not whether AI will shape healthcare. It is already doing so. The question is whether we shape that transformation deliberately – in line with British principles of safety, accountability, and equity – or allow it to happen unevenly.

The opportunity is significant. So too is the responsibility.

If we align infrastructure, regulation, funding, and culture, the UK can lead not only in discovery, but in delivery – improving outcomes for patients while strengthening our life sciences ecosystem for the future.

Get Involved

To find out more about the UKAI Healthcare and Life Sciences Working Group, contact Partnerships Director, Ben McDermott at benmcdermott@ukai.co.

Rt Hon Andrew Stephenson CBE

Chair, Curia, Health, Care and Life Sciences Research Group

Following the publication of AI Is Ready. Is the System? report by Curia and UKAI, Chair of Curia’s Health, Care and Life Sciences Research Group and former Minister of State at the Department of Health and Social Care, Andrew Stephenson writes that the NHS is well positioned to lead in AI-driven healthcare, but the challenge has shifted from innovation to implementation.

Across government, the NHS, academia, and industry, there is broad agreement that AI and advanced data science will transform healthcare and life sciences, particularly within the NHS. The science is advancing rapidly. British universities are among the strongest in the world. Our life sciences sector contributes more than £100 billion to the economy and supports hundreds of thousands of skilled jobs.[i] We have longitudinal health records, high GP registration, and a unique ability to link data across the life course. In many respects, we are better positioned than almost any nation, especially considering the advancements in the NHS.

And yet, as these discussions make clear, the central challenge is no longer invention. It is implementation.

From Innovation to Implementation: Why the NHS Must Move Beyond Pilots

Too often, innovation in the NHS remains confined to pilots. Promising technologies are tested, evaluated and praised – and then stall before reaching routine practice. The reasons are not mysterious. They include fragmented procurement, unclear lines of accountability, data governance complexity, workforce pressures, and, at times, a cultural instinct to equate the status quo with safety.

We must challenge that assumption directly. Doing nothing is not risk-free. In a health system and NHS facing rising demand, workforce shortages, and widening inequalities, standing still carries consequences of its own. Innovation, when properly evaluated and safely deployed, is not a threat to patient safety – it is an essential route to improving it.

Aligning NHS Regulation, Infrastructure and Growth to Deliver AI at Scale

Throughout these roundtables, three themes emerged repeatedly.

First, system readiness matters as much as technological capability. AI tools do not deploy themselves. They depend on infrastructure, workforce confidence, digital maturity, and governance that is proportionate rather than paralysing. Building the bridge from innovation to adoption requires effort on both sides.

Second, regulatory reform must strike the right balance. We must be safe, but we must also be fast and trusted. The regulatory framework for medical devices was not designed with adaptive AI in mind. We therefore need approaches that allow continuous monitoring, post-market learning, and clear accountability, without creating unnecessary delay. Businesses need clarity, boards need assurance, and patients need confidence.

Third, we must align economic growth with NHS transformation. Startups and scaleups cannot wait two years for data access while their runway expires. Equally, trusts cannot be expected to underwrite infrastructure without national support. If we want Britain to retain sovereign capability in AI-enabled healthcare, we must ensure that procurement pathways, data environments, and funding models enable responsible domestic innovation to scale.

Prevention and predictive medicine are particularly instructive. The science in genomics and risk stratification is advancing rapidly. Yet our funding structures in the NHS remain weighted toward treating illness rather than anticipating it. If we are serious about shifting from reactive to preventative healthcare, budgetary and accountability frameworks must evolve accordingly.

As Chair of Curia’s Health, Care and Life Sciences Research Group, my focus is on turning policy into practice. It is not enough to announce strategies. We must translate ambition into delivery at trust, system, and national level.

The discussions summarised in this report are candid – but practical. They highlight barriers to the adoption of AI in the NHS, but they also demonstrate appetite for change. Clinicians want tools that give them more time with patients. Innovators want clarity and partnership. Policymakers want solutions that improve outcomes and support growth.

Our task now is to convert shared insight into coordinated action. If we do so, the UK can become not just a leader in AI research, but a leader in responsible, system-wide deployment – improving patient care, strengthening our healthcare and life sciences sectors, and ensuring the NHS remains sustainable for generations to come.

References

[i] https://www.gov.uk/government/news/life-sciences-sector-plan-to-grow-economy-and-transform-nhs

However, while AI innovations are promising, the report says systemic barriers remain in translating these innovations into large-scale solutions across the NHS. The AI if Ready. Is the System? report, compiled by UKAI and Curia, offers a roadmap to overcome these barriers, aligning infrastructure, regulation, and investment. The recommendations outlined are not just healthcare-specific but also present significant opportunities for business growth and economic development within the life sciences sector.

The UK is renowned for its leadership in life sciences research and AI innovation. However, translating these strengths into large-scale, practical applications within the NHS remains a challenge. Despite numerous successful pilots and cutting-edge AI tools ready for deployment, systemic barriers in governance, regulation, and infrastructure are slowing their widespread adoption.

This report, a collaboration between UKAI and Curia, examines the key challenges and opportunities in scaling AI within the healthcare system, highlighting the vital need for coordinated efforts across industry, government, and healthcare providers. The findings are not just critical for healthcare reform but also for the broader economic agenda, offering businesses and policymakers a clear framework to drive growth in AI and life sciences.

Key Insights from the Report:

1. Unlocking the Potential of AI in Healthcare

AI’s potential in healthcare is undeniable, from reducing clinical workload to improving patient outcomes through predictive diagnostics and genomic medicine. However, the UK’s ambition must shift from experimenting with AI to fully integrating these innovations into healthcare infrastructures. The need for a robust digital ecosystem that allows for seamless data sharing, real-time monitoring, and scalable AI tools is urgent.

“To turn AI from a promising innovation into a healthcare revolution, we must align infrastructure, regulation, and funding. Only then can we achieve the transformative impact we need for both patients and the economy.” Rt Hon Andrew Stephenson CBE, Chair, Curia, Health, Care, and Life Sciences Research Group

“To turn AI from a promising innovation into a healthcare revolution, we must align infrastructure, regulation, and funding. Only then can we achieve the transformative impact we need for both patients and the economy.” Rt Hon Andrew Stephenson CBE, Chair, Curia, Health, Care, and Life Sciences Research Group

For businesses, AI presents a significant opportunity: by developing solutions that integrate with the NHS’s digital infrastructure, companies can position themselves as leaders in AI-driven healthcare transformation. This is especially true for startups and scaleups that can provide flexible, scalable technologies capable of addressing fragmented data systems and siloed digital environments within the NHS.

2. System Readiness: A Key Business Consideration

While AI technologies are advancing, the readiness of the healthcare system to integrate them is inconsistent. The report identifies the lack of interoperability and fragmented governance as major obstacles to AI adoption. To overcome these, the UK must treat data infrastructure and interoperability as national priorities.

At one of the Parliamentary events, host and Member of Parliament for Morecambe and Lunesdale, Lizzie Collinge MP championed the North West economy highlighting that “the UK’s ability to lead in AI-enabled healthcare depends on overcoming not just technical challenges but systemic barriers.

“By aligning AI with business and industrial strategy, we can ensure that the country remains at the forefront of healthcare innovation, driving both improved patient outcomes and economic growth”.

For businesses involved in digital infrastructure or healthcare IT solutions, there is a growing market for services that facilitate interoperability, data integration, and secure digital environments. By creating solutions that meet the NHS’s needs for unified, seamless digital systems, companies can support the transition to AI-enabled care while positioning themselves as key players in the digital health ecosystem.

3. Regulatory Agility: Balancing Innovation and Safety

Regulation plays a pivotal role in ensuring that AI tools are deployed safely within the NHS. However, as the report highlights, current frameworks are not designed to accommodate adaptive AI technologies. There is a need for a flexible, iterative regulatory approach that balances speed with safety.

“The UK’s future in AI-driven healthcare depends on collaboration across sectors. By ensuring clear governance and empowering clinicians, we can accelerate the responsible deployment of AI, enhancing both patient care and our global competitiveness.” Adama Ibrahim, UKAI, Life Sciences Advisory Board

“The UK’s future in AI-driven healthcare depends on collaboration across sectors. By ensuring clear governance and empowering clinicians, we can accelerate the responsible deployment of AI, enhancing both patient care and our global competitiveness.” Adama Ibrahim, UKAI, Life Sciences Advisory Board

For businesses in the healthcare and AI sectors, the regulatory landscape offers both challenges and opportunities. Clear and adaptive regulatory processes will enable faster deployment of AI tools, allowing businesses to innovate without being stifled by outdated regulations. This also presents an opportunity to engage with regulators to help shape the future of AI regulation in healthcare.

Strategic Opportunities for Business Growth

1. Infrastructure as a National Asset

The UK’s digital health infrastructure needs to be treated as a national asset. Investing in federated, interoperable platforms, and secure data environments (SDEs) will enable AI tools to function effectively at scale. For businesses, this presents an opportunity to partner with the NHS and government to build AI infrastructure, offering long-term growth prospects.

Moreover, AI developers can play a key role in ensuring that AI solutions are integrated into this infrastructure in a way that maximises their potential, improving both clinical outcomes and operational efficiency.

2. Aligning AI with Industrial Strategy

AI is more than just a tool for improving healthcare – it is a key driver of economic growth. The UK’s industrial strategy must align with the digital transformation of healthcare to ensure that the country remains a global leader in AI innovation. By focusing on developing AI tools that address specific NHS needs, businesses can contribute to the UK’s economic growth while improving the sustainability of the healthcare system.

The report makes it clear that responsible AI deployment within the NHS is not a trade-off between public service and economic growth. Instead, it is an opportunity to advance both, with businesses playing a key role in driving the transformation.

Companies that can navigate regulatory challenges, streamline procurement processes, and demonstrate measurable impact will be well-positioned to capitalise on this market.

3. Reimagining Prevention and Predictive Healthcare

AI-driven genomics and predictive medicine are reshaping how healthcare systems approach prevention. However, as the report highlights, the UK’s current funding models prioritise acute care over prevention, making it difficult to scale predictive tools.

For businesses in the life sciences and AI sectors, there is a clear opportunity to lead in the development of predictive models that can be integrated into existing healthcare systems. Additionally, companies can explore how to influence policy discussions around prevention funding and develop solutions that address the structural barriers in healthcare financing.

Conclusion: Moving from Innovation to Scale

The UK is well-positioned to lead the world in AI-enabled healthcare, but significant structural reforms are necessary to turn this potential into reality. By aligning infrastructure, regulation, and funding with the nation’s ambitions for AI, businesses can play a pivotal role in transforming the healthcare system while driving economic growth.

For businesses and policymakers, the challenge highlighted by this report is to work together to overcome the systemic barriers that are currently preventing AI from achieving its full potential. The opportunities for innovation, economic growth, and improving patient outcomes are immense. With the right strategy, the UK can lead the way in delivering AI at scale across healthcare systems, ensuring that innovation translates into long-term impact.

At a roundtable with leading firms including Snapchat, Meta, YouTube and TikTok on Monday 9 March, Technology Secretary Liz Kendall MP warned companies that failing to act decisively could result in further intervention from government.

The meeting comes amid growing concern about misogyny, harassment and image-based abuse on digital platforms, and follows a series of legislative and regulatory measures introduced in recent months.

Secretary of State for Science, Innovation and Technology, Liz Kendall said:

“Every woman and girl deserves to be safe online and we will stop at nothing to ensure the digital world is working for them, not against them.

“This Government has taken tough action to tackle intimate image abuse, deepfakes and the online harms women and girls face every day.

Now, tech companies must go above and beyond to use the tools readily available to them to make their platforms safer. If they don’t, these companies are not innocent bystanders – they are enabling abuse to thrive.

That is why we are asking Ofcom to report swiftly on how companies are complying, because better safety and better accountability go hand in hand.”

New legal powers targeting online abuse and deepfakes

The warning follows a series of recent government interventions aimed at addressing online violence against women and girls.

Over the past six months, ministers have taken steps to strengthen protections under the Online Safety Act, making intimate image abuse, cyberflashing and choking priority offences. These offences are now treated with the same seriousness as child abuse or terrorism in terms of platform responsibilities.

Earlier this year, the Prime Minister publicly criticised the AI platform Grok after illegal sexualised images of women and girls circulated on the site. Within days, the Government fast-tracked legislation to ban the creation of non-consensual intimate deepfakes.

Further legal requirements now mean technology companies must remove intimate images shared without consent within 48 hours of being flagged, shifting responsibility from victims to platforms.

Meanwhile, an amendment to the Crime and Policing Bill has created a new criminal offence targeting so-called “nudification apps” – AI tools that generate synthetic sexualised images of women and girls.

Ofcom expected to name platforms failing to act

Three months ago, Ofcom published guidance outlining measures companies can take to reduce online abuse, including:

• Prompts encouraging users to reconsider harmful posts
• Limits on coordinated pile-ons
• Stronger default privacy settings
• Hash-matching technology to detect and block intimate images

The regulator is now expected to report on which platforms are failing to comply with these measures.

The Government has urged Ofcom to publish its findings as soon as possible, enabling users to make informed decisions about which platforms are prioritising safety.

Women shaping the future of technology

Alongside regulatory action, the Government is also seeking to increase women’s involvement in shaping emerging technologies.

Later this week, Liz Kendall will convene the Women in Tech Taskforce, which aims to address bias in technology design and ensure women are involved in the development of future digital platforms.

The Government has also launched a public consultation on children’s digital wellbeing, inviting parents, guardians and young people to share views on how to strengthen protections across social media, gaming platforms and AI chatbots. The consultation will inform further policy decisions later this year.

Industry leaders call for cultural change in technology companies

Industry leaders say stronger regulation must be accompanied by deeper cultural change within technology companies.

Zahra Shah, Chair of the UKAI Women in AI Working Group, said:

“The Secretary is right to set this challenge. The moment for voluntary measures has passed. If we are serious about safety, it must be woven into the fabric of technology from the outset – not added as an afterthought when harm has already been done.

“Through UKAI’s work in Parliament and with industry leaders, the collective view is clear: regulation alone is not enough. We need a cultural shift inside these companies, where protecting women and girls becomes a measure of success, not a compliance burden.

“Britain has a choice: we can lead the world in responsible AI, or we can import the mistakes of the past. UKAI will work with government and industry to ensure we lead.”

As the regulatory landscape evolves, pressure is mounting on technology companies to demonstrate that safeguarding users – particularly women and girls – is embedded at the core of how digital platforms are designed and governed.

The UK Government has announced plans to establish a new Fundamental AI Research Laboratory, backed by up to £40 million in funding, aimed at supporting ambitious scientific work that could unlock the next generation of artificial intelligence breakthroughs.

The initiative, announced by the Department for Science, Innovation and Technology (DSIT) alongside UK Research and Innovation (UKRI), will fund high risk, high reward research projects designed to address some of the most persistent challenges in Artificial Intelligence (AI) systems today – including hallucinations, limited memory and unpredictable reasoning.

Ministers say solving these technical barriers could enable AI to deliver transformative improvements across sectors such as healthcare, transport, scientific discovery and public services.

The funding will be available over six years and will be accompanied by access to the UK’s AI Research Resource computing infrastructure, providing researchers with large scale computational power worth tens of millions of pounds.

Tackling the limits of today’s AI

Artificial intelligence has rapidly moved from experimental technology to everyday use in hospitals, schools and workplaces. It is already being deployed to screen patients for cancer, optimise transport systems and accelerate scientific research.

However, experts say current systems remain constrained by fundamental weaknesses such as unreliable reasoning, hallucinations and limited memory.

The new lab will focus on rethinking how AI systems are built, rather than simply scaling up existing models with larger datasets and computing resources. Researchers will be encouraged to pursue new approaches that could make future systems more accurate, transparent and trustworthy.

If successful, these advances could support earlier medical diagnoses, more resilient infrastructure, faster scientific discovery and better digital tools for everyday use.

Government seeks bold ideas from researchers

Applications for the new research laboratory are now open, with the Government inviting AI experts across the UK to put forward ambitious proposals.

The programme will support the kind of foundational research that can take years to bear fruit but has the potential to unlock entirely new capabilities in artificial intelligence.

AI Minister Kanishka Narayan MP said the investment reflects the Government’s ambition for the UK to remain at the forefront of global AI development.

He said:

“AI is already doing things we could never have imagined just a few years ago, like helping to diagnose cancer. It can and will do even more – but if we want this technology to be a force for good, we need to make sure the next big AI breakthroughs are made in Britain.

“This is a long term investment in the brilliant minds who will keep the UK in the AI fast lane. If we are the ones breaking new ground on what AI can do, we can make sure our values are baked in from the outset. This is a critical part of our mission to make AI work for everyone.”

Expert panel to review proposals

Applications will be assessed by a peer review panel chaired by Raia Hadsell, Vice President of Research at Google DeepMind and a government AI ambassador.

Hadsell emphasised the importance of foundational research in unlocking AI’s full potential.

She said: “AI has the ability to solve humanity’s most complex problems, and fundamental research that helps this technology achieve its full potential is key. The UK has the world class talent and academic ecosystem to drive transformational research, and I am excited to see the proposals that emerge from this call.”

Part of a wider national AI strategy

The new laboratory forms an early step in delivering UKRI’s recently published AI Strategy, which aims to strengthen the UK’s research leadership in artificial intelligence.

The strategy commits £1.6 billion over the next four years to support AI research, infrastructure and skills development across mathematics, computer science and engineering.

Dr Kedar Pandya, Executive Director of the Strategy Directorate at the Engineering and Physical Sciences Research Council (EPSRC), said the investment builds on the UK’s existing strengths in foundational research.

He said: “Fundamental research enables long term breakthroughs in AI. The UK’s capability rests on exceptional talent and world leading university excellence, which underpin today’s systems and will power the next generation of technologies. By backing ambitious, ground breaking work, the new Fundamental AI Research Laboratory will unlock fresh capabilities, strengthen trust and reliability, and help the UK remain at the forefront of advancing AI for society and the economy. This investment builds on a global reputation in mathematics, computer science, and engineering, supporting bold, high reward ideas that can shape the future of AI.”

Chief Executive of the UK’s trade association for the AI economy, UKAI, Tim Flagg welcomed the announcement: “This is a welcome investment in the UK’s future capability to lead in AI. The UK consistently punches above its weight in AI research and development, thanks to our world-class universities and exceptional talent.

“The real opportunity now is to ensure those breakthroughs move from the lab into the market, connecting university research with businesses that can scale these innovations, and ensuring government plays its role by adopting and procuring AI solutions across the public sector. If we get that pipeline right, this investment in fundamental research can translate into the next generation of world-class AI companies, positioning the UK as a global innovation leader and ensuring the breakthroughs discovered here are also built, scaled and deployed here.”

AI research already delivering real world impact

UKRI backed AI research is already being deployed across critical infrastructure and healthcare.

Examples include the RADAR AI system, which detects faults on the UK railway network in real time, and the IXI Brain Atlas, a dataset helping researchers analyse brain scans across more than 40 clinical trials investigating degenerative diseases such as Alzheimer’s.

With international competition in artificial intelligence accelerating, the Government hopes the new research lab will help ensure the UK remains a leading centre for cutting edge AI development while supporting economic growth, public sector innovation and scientific discovery.

Tim Flagg

Chief Executive, UKAI

The UK does not need the world’s largest data centres – it needs the most intelligent ones. In this article, Chief Executive of the UK’s AI trade Association, Tim Flagg sets out how integrated infrastructure, smarter energy pricing and transparent standards can turn climate constraints into competitive advantage.

The recent debate around AI data centres and climate change raises an important question: can the UK expand its AI capability without undermining its environmental commitments?

The honest answer is this – it depends entirely on how we design the system.

Artificial intelligence (AI) is often discussed as if it were intangible. In reality, AI runs on physical infrastructure. It requires electricity, cooling, fibre networks, land, engineers, and long-term investment. That reality has led some to conclude that AI data centres are inherently at odds with climate policy.

That conclusion is premature.

The UK does not face a choice between climate leadership and AI leadership. But it does face a choice between fragmented infrastructure delivery and intelligent system design.

“The true risk is not that AI uses energy. The risk is that we continue to plan energy, digital infrastructure, grid access, water use and skills in silos.”

The true risk is not that AI uses energy. The risk is that we continue to plan energy, digital infrastructure, grid access, water use and skills in silos. When infrastructure is built in isolation, bottlenecks emerge, costs rise and public trust erodes. When it is designed as a connected system, constraints become drivers of innovation rather than brakes on growth.

From scale to system design

Britain’s structural conditions actually point towards a distinctive opportunity. We have high and volatile electricity prices, grid constraints, and planning sensitivities. These are often framed as disadvantages. In fact, they push us towards efficiency.

If the UK tried to compete on sheer hyperscale compute volume alone, we would struggle against countries with cheaper power. But if we compete on efficiency – AI that delivers measurable value per unit of energy consumed – we can build a globally relevant model.

This is what we mean by ‘Green AI’, as we set out in our recent report: AI, Energy and Infrastructure: Building a Green AI Superpower. AI that is energy-efficient, affordable, deployable at scale and aligned with long-term economic and environmental sustainability. Innovation drives this efficiency, across areas such as chip design, grid management, smaller language models, modular data centres and heat re-use. The UK can lead by bringing these innovations together.

The climate debate rightly focuses on electricity demand. Data centres require continuous power, and AI workloads are growing. But the UK’s problem is not simply generation capacity. It is market design.

Energy markets, not energy shortages

Wholesale electricity prices remain tied to gas through marginal pricing, even as the share of low-carbon generation increases. This means electricity prices can remain elevated and volatile even when renewables are abundant. For long-lived AI infrastructure, price volatility is as damaging as scarcity. Investors require predictable operating costs over 10 to 20 years.

Targeted reform – expanding long-term fixed-price arrangements, reducing exposure to gas-linked volatility, and investing in grid reinforcement, storage, and flexibility – would materially reduce system risk. These are not AI-specific subsidies. They are structural energy reforms that benefit households and industry alike.

Great British Energy, if used intelligently, could play a stabilising role. Not by offering preferential discounts to data centres, but by accelerating low-cost clean generation, supporting long-term contracting, and strengthening system resilience. That reduces risk for everyone.

Designing for legitimacy: water, planning and place

Water usage is another concern often raised. It is important to treat it seriously. In parts of the East and South East, water stress is real. But design choices matter. Closed-loop and dry cooling systems are already widely available. Transparent reporting on water usage effectiveness can replace speculation with evidence. Early integration of cooling strategy into planning decisions reduces the risk of local opposition driven by mistrust.

Planning reform will be critical. Speed alone is not the objective. Integration is. A data centre should not be treated as a warehouse with an unusually large plug. It should be assessed as part of a combined digital and energy system underpinning economic productivity and public services. Where projects bring together behind-the-meter renewables, storage, grid reinforcement, and connectivity as a coherent scheme, planning decisions become more robust and less contentious.

Equally important is demand discipline. Not all AI workloads deliver equal economic value. The UK should anchor infrastructure growth to high-impact use cases – health services, energy optimisation, public administration, and advanced manufacturing – rather than speculative capacity built on headline projections. Evidence-based demand modelling and aggregated public sector procurement can reduce overbuild while strengthening national capability.

Efficiency is not a constraint on ambition. It is a competitive strategy.

Efficiency as the UK’s competitive advantage

In a world where electricity, grid capacity and public legitimacy are increasingly scarce, the ability to deliver useful AI outcomes with less energy, less water and lower systemic risk will define long-term leadership. Many countries face similar, increasing structural pressures. Few can afford unlimited hyperscale abundance. The UK can become an exporter of efficient, well-governed AI systems precisely because we are forced to design intelligently.

Transparency will also matter. Standard reporting on power usage effectiveness, water usage effectiveness and carbon intensity should become normal practice. Clear metrics build trust. They also create performance incentives that reward operators who innovate in efficiency.

Building an intelligent AI infrastructure

The UK does not need to build the world’s largest AI infrastructure. It needs to build the most intelligent one.

That means recognising AI infrastructure as part of critical national systems. It means aligning planning reform with grid reform and skills development. It means treating digital connectivity as core infrastructure. It means embedding community benefit and local engagement into project design from the outset. And it means reforming energy markets so that clean generation translates into stable, competitive prices.

“The UK does not need to build the world’s largest AI infrastructure. It needs to build the most intelligent one.”

The alternative is not environmental protection. It is strategic drift.

If investment flows elsewhere because we fail to address volatility and integration, the UK will still consume AI services – but the economic value, jobs and technical capability will sit offshore. Climate impact does not disappear simply because infrastructure is built in another jurisdiction. It merely moves.

Britain has the research base, regulatory credibility, and institutional depth to lead in Green AI. But leadership will not emerge automatically. It requires deliberate system design.

The climate concerns being raised are legitimate. They are precisely why we must get this right.

AI can strengthen energy systems, optimise grids, improve public services, and accelerate scientific discovery. But only if the infrastructure that powers it is designed with discipline, transparency, and integration.

This is not a choice between growth and responsibility. It is a test of whether we can deliver both. UKAI believes that the UK can and should be a leader in delivering that responsible growth.

OpenAI and Microsoft have formally joined the UK’s international coalition to safeguard the development of advanced artificial intelligence, pledging new funding to the AI Security Institute’s (AISI) flagship Alignment Project.

Announced at the AI Impact Summit in India by the Deputy Prime Minister David Lammy and AI Minister Kanishka Narayan, the move sees an additional £5.6 million from OpenAI alongside further support from Microsoft and other partners.

The new commitments mean more than £27 million is now available for AI alignment research, supporting around 60 projects across eight countries, with a second funding round due to open later this year.

The Government believes this initiative reinforces the UK’s ambition to remain at the forefront of frontier AI research while ensuring that safety, control and public trust remain central to deployment.

What Is AI Alignment – And Why It Matters

AI alignment refers to the challenge of ensuring that advanced AI systems act in accordance with human intentions, without unintended or harmful behaviour.

As models grow more capable and autonomous, the technical difficulty of keeping them reliable and controllable increases. Alignment research focuses on developing methods to prevent unsafe outcomes as AI systems are deployed in increasingly complex and open-ended environments.

Without continued progress in alignment, increasingly powerful AI systems could act in ways that are difficult to anticipate or govern – creating challenges not just for companies, but for regulators and governments worldwide.

The UK government has positioned alignment as essential to building public confidence in AI technologies that are already reshaping public services, reducing medical scan times, and driving productivity gains across sectors.

Ministerial Backing: “Safety Baked In from the Outset”

Deputy Prime Minister David Lammy emphasised that safety remains central to the UK’s AI strategy.

“AI offers us huge opportunities, but we will always be clear-eyed on the need to ensure safety is baked into it from the outset.”

He added that the UK has built “strong safety foundations” and said support from OpenAI and Microsoft would be “invaluable” in advancing that effort.

AI Minister Kanishka Narayan framed trust as the defining challenge of AI adoption.

“We can only unlock the full power of AI if people trust it… alignment research tackles this head-on.”

Narayan described trust as “one of the biggest barriers to AI adoption”, arguing that the expanded funding will ensure AI delivers benefits “safely, confidently and for everyone”.

Welcoming the news, CEO of UKAI, the AI trade association in the UK, Tim Flagg said “This is a welcome and important step towards building trusted, secure AI systems, and it reinforces the UK’s leadership at the forefront of global AI safety and security. The Alignment Project shows how government, academia and industry – both major international firms and innovative UK businesses – can work together to set high standards that benefit everyone. With the right continued investment and collaboration, AI security can become a defining UK strength and a major export, positioning Britain as a trusted partner to countries around the world as they adopt AI safely and responsibly.”

OpenAI: No Single Organisation Can Solve Alignment Alone

For OpenAI, the decision to back the Alignment Project reflects a broader recognition that safety cannot be solved internally by any one firm.

Mia Glaese, Vice President of Research at OpenAI, said:

“As AI systems become more capable and more autonomous, alignment has to keep pace.”

She stressed that “the hardest problems won’t be solved by any one organisation working in isolation”, adding that independent research teams testing different approaches are essential to building a reliable and controllable AI ecosystem.

The company’s support for AISI complements its own internal alignment work, strengthening what it described as a broader research ecosystem focused on keeping advanced systems safe as they scale.

An Expanding International Coalition

Beyond OpenAI and Microsoft, the Alignment Project is supported by a wide international network, including:

• Canadian Institute for Advanced Research (CIFAR)
• Amazon Web Services (AWS)
• Anthropic
• UK Research and Innovation (UKRI)
• Advanced Research and Invention Agency (ARIA)

The advisory board features leading global researchers including Yoshua Bengio, Zico Kolter, Shafi Goldwasser and Andrea Lincoln, alongside figures from academia and frontier AI labs.

The first 60 funded projects span eight countries, demonstrating the UK’s ambition to shape global standards rather than act alone.

Cementing the UK’s Leadership in Frontier AI

The Alignment Project combines grant funding, access to compute infrastructure and academic mentorship from AISI’s own scientists. The goal is to accelerate progress in alignment while ensuring researchers can test and evaluate increasingly powerful models responsibly.

As home to world-leading AI firms and four of the world’s top ten universities, the UK sees itself as uniquely placed to convene global partners around shared safety principles.

At a time when AI is rapidly being integrated into public services, defence, finance and healthcare, alignment is emerging as one of the defining technical and governance challenges of the decade.

The UK’s bet is that public confidence and global competitiveness are not in tension – but interdependent.

By securing backing from two of the world’s most influential AI companies, ministers are signalling that responsible innovation and national renewal can advance together.

Whether alignment research keeps pace with accelerating capability remains one of the most important questions facing the global AI community.

The North West has long been recognised as one of the UK’s most promising regions for the development of the artificial intelligence (AI) economy. It is home to globally respected universities, internationally recognised research centres, and a fast-growing community of start-ups and scale-ups applying AI across health, manufacturing, energy, and transport.

Yet despite these strengths, the region has struggled to convert research excellence and entrepreneurial energy into widespread economic impact. According to a new report published by policy institute Curia, in partnership with AI trade association, UKAI, that gap is not a failure of ambition, but the result of structural barriers that prevent AI adoption from scaling across the real economy.

The Get Britain Growing: North West Conference AI Sprint Report brings together findings from a policy sprint workshop held in Liverpool last year, which convened parliamentarians, metro mayors, investors, academics, technology firms, and public sector leaders.

The central question the sprint was designed to ask: how can AI be used to drive long-term, inclusive growth in the North West?

Skills Remain the Biggest Constraint on AI Adoption

The report identifies the skills gap as the most immediate and widespread barrier to AI-driven growth. While the national debate often focuses on shortages of highly specialised machine learning engineers, participants in the sprint argued that the bigger challenge lies elsewhere.

Most near-term productivity gains from AI depend on everyday adoption by managers, frontline workers, and public servants who are confident working with data, understand the limits of AI tools and can apply those tools to real operational problems. Across sectors, employers reported difficulty recruiting and training staff with this applied capability.

This important report highlights systemic misalignment between education providers and employer demand. School curricula do not sufficiently prepare students with the mathematical and data literacy needed to engage with AI tools. Universities often prioritise narrow technical expertise over broader, sector-specific skills. Meanwhile, businesses struggle to navigate a fragmented training landscape, with little clarity on which courses deliver practical value.

To address this, the report calls for a regional AI skills strategy spanning schools, apprenticeships, universities, and mid-career retraining. This would embed AI literacy as a core competence, rather than treating AI as a specialist or abstract subject, and would incentivise education providers to align more closely with employer needs.

There are obvious opportunities to deliver such a strategy in regions across the UK.

Infrastructure, Energy, and Planning are Holding Back Growth

Beyond skills, the report states that AI adoption cannot scale without coordinated investment in infrastructure – particularly energy, compute, and digital connectivity.

Participants highlighted the high cost of energy, limited grid capacity, and slow planning processes as major deterrents to investment. While the UK has world-class AI research, it risks falling behind competitors in Europe, the US, and the Middle East when it comes to attracting data-intensive activity and data centre investment.

The report argues that regions that can offer predictable, affordable, and sustainable energy will have a clear competitive advantage. In the North West, this means upgrading grid capacity, investing in renewable energy storage, and making better use of brownfield sites for innovation-led development.

Crucially, infrastructure planning must be joined up. Rather than treating energy, transport, housing, and digital networks separately, the report proposes integrated “AI corridors” that combine these elements and support clustering around universities and innovation districts.

Investment is Fragmented – and the ‘Missing Middle’ Persists

Despite growing interest in AI, investment pathways in the UK remain fragmented and risk-averse, particularly outside London and the South East. The report highlights a persistent ‘missing middle’ in AI finance: companies that have secured seed funding but struggle to access the capital needed to scale.

Public procurement, which could provide early revenue for innovative AI firms, is often slow and complex, with compliance costs disproportionate to contract size. Even when pilots succeed, there is no clear route to wider adoption.

To address this, the report recommends the creation of a unified North West AI Investment Fund, coordinated at regional level and aligned with national priorities. This would not replace existing schemes, but act as a single front door for investors and businesses, matching projects with appropriate sources of public and private capital.

A regularly updated regional investment prospectus would set out opportunities across the North West, helping investors navigate what is currently an opaque and fragmented landscape.

A North West AI Hub and Pilot Scheme

At the centre of the report’s recommendations is the proposal for a North West AI Pilot Scheme, coordinated through a new North West AI Hub based in Liverpool.

The Hub would act as a regional convenor, bringing together universities, local and combined authorities, the NHS, industry, and investors. It would host training facilities, start-up incubation space, and access to high-performance compute, while also aligning skills planning, infrastructure development, and investment strategy.

Importantly, the report positions the North West as a potential national testbed for AI policy. With strong mayoral leadership and devolved powers, the region could work with central government to trial more flexible, innovation-friendly approaches to regulation, while maintaining national oversight and public trust.

From Aspiration to Delivery

The report concludes that the North West already has the foundations needed to become a national exemplar for responsible AI adoption. What has been missing is coordination – between skills and employers, infrastructure and planning, investment, and regulation.

By implementing the recommendations set out in the AI Sprint Report, the region could move beyond isolated success stories towards systemic change, ensuring that AI delivers productivity gains, high-quality jobs, and improved public services.

Policymakers, investors, and business leaders alike can work towards AI-led growth, but it will not happen by accident. It requires deliberate regional strategy, sustained collaboration, and a willingness to test new models of delivery.

To find out more about UKAI’s work convening industry, policymakers, and researchers to support responsible AI adoption across the UK, visit www.ukai.co.

Natasa Mihajlovic

Chair, UKAI Life Sciences Working Group

Following their submission to the National Commission into the Regulation of AI’s call for evidence, Chair of UKAI’s Life Sciences Working Group, Natasa Mihajlovic says AI in healthcare does not suffer from a lack of regulation so much as a lack of shared understanding about how existing rules apply once systems are live, learning, and embedded in clinical practice.

On 2 February 2026, the UKAI Life Sciences Working Group submitted a response to the Medicines and Healthcare products Regulatory Agency (MHRA) National Commission into the Regulation of AI in Healthcare Call for Evidence. That submission was informed by a roundtable held days earlier, co chaired with Curia, bringing together voices from across the NHS, regulators, industry, technology providers, and professional and policy communities.

The starting insight was a simple one. Artificial Intelligence (AI) in healthcare is already regulated. Medical device regulation, pharmacovigilance, clinical governance, and professional accountability frameworks are all in force and actively applied. The real question is how well these mechanisms cope with software driven systems that evolve over time, behave differently across settings, and blur traditional lines of responsibility.

When software behaves unlike hardware

Much of the regulatory system is built around relatively static products. AI enabled systems are different. They may update regularly, learn from new data, or be deployed in ways not fully anticipated at the point of approval.

Roundtable participants, including Dr Mani Hussain of the MHRA, explored how existing frameworks are applied in practice to software based and AI enabled medical devices. Particular attention was given to post deployment behaviour, version control, and how changes are assessed once a system is already in use.

These are not abstract concerns. In real clinical environments, performance variation across trusts, populations, or workflows can have material consequences for safety, confidence, and adoption.

Risk proportionality matters more than novelty

A consistent theme was the importance of risk-based proportionality. Not all AI is created equal, and not all uses carry the same implications.

Systems supporting administrative tasks or low risk operational decisions raise very different regulatory questions from those that influence diagnosis, treatment, or clinical decision making. Treating them as equivalent risks slows innovation where it is least dangerous, while failing to focus attention where it matters most.

Participants emphasised that proportionality already exists within regulatory frameworks, but is not always applied consistently or clearly in the context of AI.

Oversight does not end at deployment

Another area of focus was what happens after an AI system goes live. Monitoring performance over time, managing updates, and identifying emerging issues are all essential, yet often unevenly handled.

Existing vigilance concepts offer a starting point. Reporting mechanisms, incident review processes, and governance structures are already familiar to healthcare organisations. The challenge is adapting them to systems that may change incrementally rather than fail dramatically.

Without credible post deployment oversight, confidence in AI use will remain fragile, regardless of how rigorous pre market assessment may be.

Clarity of responsibility builds confidence

Responsibility across the AI lifecycle was a recurring concern. Manufacturers, healthcare organisations, and clinicians all have defined roles, but those roles can become blurred when systems are adaptive or embedded deeply into workflows.

Clear allocation of responsibility, linked to function and context of use, is essential not only for accountability but for confidence. Clinicians need to know what they are responsible for. Organisations need clarity on governance obligations. Developers need predictable expectations.

Ambiguity benefits no one.

Regulation as an ongoing conversation

The submission to the MHRA and the accompanying roundtable were practical assessments of how AI is currently regulated and used in healthcare, and where greater clarity or consistency may be needed.

For the UKAI Life Sciences Working Group, this work is a point of continuity rather than conclusion. It anchors ongoing collaboration with Curia, the MHRA, and industry around a shared objective: making AI governance workable within the realities of healthcare delivery.

The future of AI in the NHS will not be decided by whether regulation exists, but by whether it is applied in ways that reflect how healthcare actually functions, and how technology is actually used.