In October, the Connected Places Catapult hosted a roundtable event at the House of Lords, chaired by Lord Timothy Clement-Jones CBE, to discuss how the UK can realise its ambitions to be a world leader in AI innovation
The recent US state visit and signing of the Technology Prosperity Deal Memorandum of Understanding marked a step-change in UK-US cooperation on frontier technologies.
The deal brings a record £150bn in inward investment, including NVIDIA’s £2bn to catalyse the UK’s AI start-up ecosystem, alongside major commitments from Microsoft, Google and others. This investment will expand advanced AI infrastructure, create new jobs and empower the UK to compete globally.
The UK’s AI Opportunities Action Plan and Industrial Strategy articulate a vision for the UK to lead as an “AI maker, not an AI taker”. The ambition is to harness AI for economic growth, improved public services and new opportunities for citizens.
However, realising this vision requires more than capital: it demands programmatic action, cross-sector collaboration, and investment in the data infrastructure that underpins AI innovation.
Roundtable insights: Challenges and opportunities
Developing joined-up systems for AI and data innovation presents complex challenges across governance, regulation, technology, economics and culture. A central issue is the lack of cross-sector governance: there is a clear need for coordinated outcome-focused leadership that brings together regulators, public infrastructure leaders and industry to oversee data and AI initiatives and foster a healthy ecosystem.
Participants noted the urgency of integrating AI adoption with data sharing and infrastructure planning and highlighted the need for better coordination across government departments. While the UK’s Industrial Strategy and data chapter provide a mandate for change, implementation is lagging due to siloed working and lack of strategic alignment.
Regulation, funding and the role of business
A common theme throughout the roundtable was the evolving relationship between business and regulation. Participants discussed the importance of sustainable funding for regulators, suggesting that businesses benefiting from new data-driven markets should contribute to regulatory oversight.
There was consensus that businesses must play a proactive role in educating the public and stakeholders about data and AI – demystifying complex technologies, building trust and informing regulatory approaches.
The group highlighted the need for clear incentives and accountability mechanisms to ensure responsible innovation. It was noted that demonstrating clear value is often the catalyst for unlocking investment in data and AI initiatives, with participants emphasising the importance of aligning incentives and addressing gaps in current arrangements to unlock greater value.
The role of data intermediaries in empowering individuals and organisations to manage and exchange data was highlighted, with the government seeking to remove barriers and support the growth of this industry.
The discussion further underscored the importance of aligning incentives through risk and benefit sharing models, which could encourage more organisations to participate in data sharing initiatives. Past examples, such as the telecoms sector, demonstrated how industry-funded regulators and mandated education campaigns can support market transformation.
While building trust for interoperability is often resource-intensive, participants noted that unlocking value between companies can be relatively straightforward once foundational trust mechanisms are in place.
Data infrastructure: Technical and legal foundations for AI
Technological interoperability remains elusive, with no shared definition of what constitutes a joined-up system. Many initiatives continue to run in parallel without coordination, leaving organisations without the regulatory “air cover” needed to deploy AI safely and confidently.
The roundtable explored the technical and legal complexities of data sharing for AI, noting that different use cases – such as training models, fine-tuning or safety testing – require tailored data types and legal frameworks.
Participants discussed the development of data exchanges and marketplaces, including the Creative Content Exchange, as mechanisms to facilitate secure, value-driven data sharing between content owners and AI developers. These platforms are seen as vital to supporting a healthy data market in the UK.
Current data licences are often inadequate, particularly with the rise of agentic AI and synthetic data. The UK’s success with AI depends on access to high-quality, well-licensed data. Yet, existing licensing models frequently fail to account for the complexities of modern AI, underscoring the need for tailored data sharing models and technical infrastructure.
The importance of standardised approaches and interoperability was repeatedly emphasised, with reference to ongoing work by the Open Data Institute and international bodies.
The roundtable also highlighted the value in a consistent data valuation framework for the public sector, recognising data as an economic, financial and social asset, providing an effective starting point for the articulation of private sector data as an asset.
Participants stressed the importance of modernising licensing options beyond the Open Government Licence to better reflect current technological realities and enable more flexible, value-driven data sharing.
Finally, the expansion of smart data schemes, supported by £36m in funding, was discussed as a way to enable secure, consented data sharing across multiple sectors, driving both innovation and consumer benefit.
Organisational transformation and workforce readiness
The rise of AI is driving the creation of new organisational roles (eg chief data officer, chief AI officer) and expanding the remit of existing ones, particularly in HR and data governance.
Data and HR leaders are seen as increasingly pivotal in managing the workforce transition brought about by AI and automation, requiring leaders to navigate changes in skills, culture and accountability.
However, cultural and organisational barriers persist, including fear of deploying AI, resistance to change and limited mechanisms for sharing data and learning from failure. The roundtable highlighted that successful organisations are those that invest in upskilling, foster cross-functional collaboration and embrace a culture of experimentation and transparency.
Public infrastructure and standards for innovation
Robust public infrastructure is essential for a healthy data ecosystem. This includes public benchmarks, evaluation protocols and registers of best practice – resources that underpin trust, transparency and continuous improvement.
However, commercial incentives to develop these assets are limited, making multi-stakeholder collaboration vital. To ensure credibility and adoption, a governance layer comprising voices from government, industry, academia and civil society is required to enforce community-agreed standards and ensure responsible innovation.
The government’s commitment of up to £12m for cross-sectoral data sharing infrastructure initiatives was noted, particularly targeting the eight industrial strategy sectors. The National Data Library, supported by a £100m award, was also highlighted as a major initiative to enhance public sector data capability and capacity, further supporting the UK’s data-driven growth ambitions.
Participants distinguished between data infrastructure and data sharing infrastructure, noting that the latter should be treated as a public asset enabling secure and scalable data exchange between organisations.
The roundtable also discussed the challenge of aligning economic value across sectors. Unlocking value between companies requires leadership and compelling business cases to justify investment in shared data infrastructure.
Sectoral challenges and the need for regulatory “air cover”
Despite the transformative potential of data-driven innovation, a culture of risk aversion and regulatory uncertainty often slows adoption. The concept of “air cover” – regulatory support and clear accountability – was discussed as essential for enabling innovation in critical infrastructure.
Without it, even the most promising AI tools may remain unused. Regulators must provide not just rules, but reassurance and guidance to help organisations innovate with confidence.
Flexibility in infrastructure design was also emphasised, again noting the energy sector, where emerging sources of energy require adaptable systems capable of managing dynamic inputs.
Participants highlighted that fear and uncertainty around accountability remain significant barriers to deploying AI in critical environments, with concerns about responsibility if things go wrong.
Government strategy and cross-departmental coordination
Finally, the roundtable turned to the role of government in shaping the future of data and AI policy. While the UK’s Industrial Strategy provides a strong mandate, implementation is often hampered by siloed working and lack of strategic alignment.
There is an urgency to integrate AI adoption with data sharing and infrastructure planning but the cogs are not yet in motion. Participants noted the need for better coordination across government departments, possibly via a structural committee with oversight of data and AI initiatives.
Ongoing stakeholder engagement was identified as a key mechanism to maintain momentum and ensure policy remains grounded in real-world needs.
Recommendations and next steps
1. Governance and strategic oversight
The creation of a cross-sector orchestration body with representation from government, industry and academia. This body would oversee data and AI initiatives, foster a healthy ecosystem and ensure strategic alignment across sectors.
2. Standards and regulatory clarity
Accelerate the development and adoption of standardised approaches for data sharing that are AI-ready.
3. Infrastructure and public assets
Invest in public infrastructure such as benchmarks, evaluation protocols and registers of best practice, recognising sectoral nuances and regulatory environment.
4. Data valuation framework and skills development
Support organisational change by enabling enterprises to recognise data as an economic, financial and social asset. Expand smart data schemes and support the growth of data intermediaries to encourage businesses to invest in new roles and skills to manage AI’s impact.
5. Government coordination and stakeholder engagement
Enhance government coordination through cross-departmental committees or taskforces. Maintain momentum via ongoing stakeholder engagement, including regular roundtables and reporting to ensure policy remains grounded in real-world needs and implementation stays on track.
Achieving the UK’s ambition to lead in data sharing and AI innovation will require coordinated action across standards, governance, infrastructure and skills. The roundtable committed to ongoing collaboration on progress against these goals in the coming months.
Organisations taking part in the roundtable included:
- Advanced Manufacturing Research Centre
- Centre for Net Zero (Octopus Energy Group)
- CMCL
- Chrysalis Ecosystems
- Connected Places Catapult
- Department for Science, Innovation & Technology
- DNV UK
- Freshfields
- King’s College London
- Open Data Institute
- National Energy System Operator
- Sarah Hayes Independent Consultant
The Leading Voices roundtable series is hosted at the House of Lords by invitation of Merlin Hay, the Earl of Erroll, and facilitated by Connected Places Catapult and the Digital Twin Hub.
The post Accelerating the UK’s AI readiness appeared first on Planning, Building & Construction Today.
