What are the 50 recommendations in the Ai Opportunities Action Plan?

1. Set out, within 6 months, a long-term plan for the UK’s AI infrastructure needs, backed by a 10-year investment commitment.
2. Expand the capacity of the AI Research Resource (AIRR) by at least 20x by 2030 – starting within 6 months.
3. Strategically allocate sovereign compute by appointing mission-focused “AIRR programme directors” with significant autonomy.
4. Establish ‘AI Growth Zones’ (AIGZs) to facilitate the accelerated build out of AI data centres.
5. Mitigate the sustainability and security risks of AI infrastructure, while positioning the UK to take advantage of opportunities to provide solutions.
6. Agree international compute partnerships with like-minded countries to increase the types of compute capability available to researchers and catalyse research collaborations.
7. Rapidly identify at least 5 high-impact public datasets it will seek to make available to AI researchers and innovators.
8. Strategically shape what data is collected, rather than just making data available that already exists.
9. Develop and publish guidelines and best practices for releasing open government datasets which can be used for AI, including on the development of effective data structures and data dissemination methods.
10. Couple compute allocation with access to proprietary data sets.
11. Build public sector data collection infrastructure and finance the creation of new high-value datasets that meet public sector, academia and startup needs.
12. Actively incentivise and reward researchers and industry to curate and unlock private datasets.
13. Establish a copyright-cleared British media asset training data set.
14. Accurately assess the size of the skills gap.
15. Support Higher Education Institutions to increase the numbers of AI graduates and teach industry-relevant skills.
16. Increase the diversity of the talent pool.
17. Expand education pathways into AI.
18. Launch a flagship undergraduate and masters AI scholarship programme on the scale of Rhodes, Marshall, or Fulbright for students to study in the UK.
19. Ensure its lifelong skills programme is ready for AI.
20. Establish an internal headhunting capability on a par with top AI firms to bring a small number of elite individuals to the UK.
21. Explore how the existing immigration system can be used to attract graduates from universities producing some of the world’s top AI talent.
22. Expand the Turing AI Fellowship offer.
23. Continue to support and grow the AI Safety Institute (AISI) to maintain and expand its research on model evaluations, foundational safety and societal resilience research.
24. Reform the UK text and data mining regime so that it is at least as competitive as the EU.
25. Commit to funding regulators to scale up their AI capabilities, some of which need urgent addressing. Government should also ensure all sponsor departments demonstrate how they are funding this capability within their budgets through the Spending Review process.
26. Ensure all sponsor departments include a focus on enabling safe AI innovation in their strategic guidance to regulators.
27. Work with regulators to accelerate AI in priority sectors and implement pro-innovation initiatives like regulatory sandboxes.
28. Require all regulators to publish annually how they have enabled innovation and growth driven by AI in their sector.
29. Support the AI assurance ecosystem to increase trust and adoption.
30. Consider the broader institutional landscape and the full potential of the Alan Turing Institute to drive progress at the cutting edge, support the government’s missions and attract international talent.
31. Appointing an AI lead for each mission to help identify where AI could be a solution within the mission setting, considering the user needs from the outset.
32. A cross government, technical horizon scanning and market intelligence capability who understands AI capabilities and use-cases as they evolve to work closely with the mission leads and maximise the expertise of both.
33. Two-way partnerships with AI vendors and startups to anticipate future AI developments and signal public sector demand.
34. Consistent use of a framework for how to source AI – whether to build in-house, buy, or run innovation challenges – that evolves over time, given data, capability, industry contexts and evaluation of what’s worked.
35. A rapid prototyping capability that can be drawn on for key projects where needed, including technical and delivery resource to build and test proof of concepts, leveraging in-house AI expertise, together with specialists in design and user experience.
36. Specific support to hire external AI talent.
37. A data-rich experimentation environment including a streamlined approach to accessing data sets, access to language models and necessary infrastructure like compute.
38. A faster, multi-stage gated and scaling AI procurement process that enables easy and quick access to small-scale funding for pilots and only layers bureaucratic controls as the investment-size gets larger.
39. A scaling service for successful pilots with senior support and central funding resource.
40. Mission-focussed national AI tenders to support rapid adoption across de-centralised systems led by the mission delivery boards.
41. Development or procurement of a scalable AI tech stack that supports the use of specialist narrow and large language models for tens or hundreds of millions of citizen interactions across the UK.
42. Mandating infrastructure interoperability, code reusability and open sourcing.
43. Procure smartly from the AI ecosystem as both its largest customer and as a market shaper.
44. Use digital government infrastructure to create new opportunities for innovators.
45. Publish best-practice guidance, results, case-studies and open-source solutions through a single “AI Knowledge Hub”
46. In the next 3 months, the Digital Centre of Government should identify a series of quick wins to support the adoption of the scan, pilot scale approach and enable public and private sector to reinforce each other.
47. Leverage the new Industrial Strategy. The development of a new Industrial Strategy presents an opportunity to drive collective action to support AI adoption across the economy.
48. Appoint AI Sector Champions in key industries like the life sciences, financial services and the creative industries to work with industry and government and develop AI adoption plans.
49. Drive AI adoption across the whole country.
50. Create a new unit, UK Sovereign AI, with the power to partner with the private sector to deliver the clear mandate of maximising the UK’s stake in frontier AI.