Record STMT-WA8FBD6Aspirational

Growing the Artificial Intelligence Industry in the UK

GROWING THE ARTIFICIAL INTELLIGENCE INDUSTRY IN THE UK

Report State lawNorthern Europe · GBadopted

This review examines how to grow the artificial intelligence industry in the United Kingdom by addressing challenges in data access, skills supply, research commercialization, and industry uptake. Authored by Professor Dame Wendy Hall and Jérôme Pesenti, the report sets out 18 recommendations for government, industry, and academia to work together. It highlights potential economic and social benefits of AI and proposes measures such as establishing Data Trusts, creating AI fellowships, and launching an industry-funded Master's program.

Summary and content fields are drawn from the document text and are pending editorial review.

Who issued it

Department for Science, Innovation and TechnologyGovernment

Lead issuer

Department for Digital, Culture, Media & SportGovernment (executive) · GB

Co-issuer

Legal forceAspirational

Under whose authorityState law

Judged fromfull text

Who it governs

National governmentPublic sector bodiesCompaniesAI developers and providersResearchers and academics

Policymakers, industry leaders, academic researchers, and public sector bodies seeking guidance on fostering artificial intelligence capabilities and economic growth in the UK.

Sectors

Cross-sectorResearch and science · artificial intelligence and data science research

What the document contains

What's covered

The document addresses the strategic conditions required to grow the artificial intelligence industry in the UK, focusing on four primary pillars: improving access to data through Data Trusts and open formats, expanding the supply of AI skills across higher education and diversity initiatives, maximizing AI research and commercialization via the Alan Turing Institute and intellectual property transfer, and supporting broader uptake of AI through public sector readiness and industry guidance.

What's missing

Detailed technical definitions of machine learning architectures, binding legislative enforcement mechanisms for algorithmic ethics, and a comprehensive review of the impact of automation on workforce displacement.

Key takeaways

The UK possesses strong foundational research in artificial intelligence but needs to act decisively to remain a global leader.
Establishing Data Trusts and improving machine-readable public research data can enhance secure and mutually beneficial data sharing.
A step-change is required in skills training, including industry-funded Master's programmes, conversion degrees, and dedicated PhD places.
The Alan Turing Institute should expand to become the national institute for artificial intelligence and data science.
A UK AI Council should be established to coordinate growth, improve understanding, and foster non-competitive collaboration across sectors.

Principles it states

Promote human flourishing as an overarching guide for data and AI systems.Protect individual and collective rights and interests.Ensure that trade-offs affected by data management and use are made transparently, accountably, and inclusively.Seek out good practices and learn from success and failure.Enhance existing democratic governance.

Outline

· Foreword
· Executive Summary
· Summary of Recommendations
· Section One: Artificial Intelligence and Objectives of this Review
· Section Two: Overview of Current Use of AI, Markets and Support for Growth
· Section Three: Recommendations to Improve Access to Data
· Section Four: Recommendations to Improve Supply of Skills
· Section Five: Recommendations to Maximise AI Research and Commercialisation
· Section Six: Recommendations to Support Uptake of AI
· Conclusion
· Acknowledgements

Issued15 October 2017

Length27,895 words

FormatNot recorded

Scopenational

How it scores

Pending review

Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.

Accountability

3/5

Clear responsibility for AI outcomes

Trust, ethics, governance and algorithmic accountability: Resolving ethical and societal questions is beyond the scope

SECTION ONE: ARTIFICIAL INTELLIGENCE AND OBJECTIVES OF THIS REVIEW

screening score · 2026-10-23

Fairness

3/5

Non-discrimination and equitable treatment

Government, industry and academia must embrace the value and importance of a diverse workforce for AI, and should work together to break down stereotypes and broaden participation.

RECOMMENDATIONS TO IMPROVE SUPPLY OF SKILLS

screening score · 2026-10-23

Human Dignity

2/5

Respect for the inherent worth of persons

The promotion of human flourishing is the overarching principle that should guide the development of systems of data governance.

SECTION ONE: ARTIFICIAL INTELLIGENCE AND OBJECTIVES OF THIS REVIEW

screening score · 2026-10-23

Human Oversight

0/5

Humans remain in control of consequential decisions

screening score · 2026-10-23

Privacy

3/5

Protection of personal data and private life

It would be necessary to address concerns over the privacy and protection of sensitive health data.

SECTION ONE: ARTIFICIAL INTELLIGENCE AND OBJECTIVES OF THIS REVIEW

screening score · 2026-10-23

Transparency

3/5

Openness about how AI systems work and are used

The Information Commissioner’s Office and the Alan Turing Institute should develop a framework for explaining processes, services and decisions delivered by AI, to improve transparency and accountability.

RECOMMENDATIONS

screening score · 2026-10-23

Enforcement

1/5

Consequences and compliance mechanisms with real force

clarify, enforce and remedy

SECTION ONE: ARTIFICIAL INTELLIGENCE AND OBJECTIVES OF THIS REVIEW

screening score · 2026-10-23

Impact Assessment

0/5

Required assessment of an AI system's risks/impacts before or during use

screening score · 2026-10-23

Topics

Physical AI Governancecontext

artificial_intelligence industrial_strategy data_governance skills_development research_and_development