The UK’s AI Governance Strategy: Building Trust as Infrastructure
This study provides a systematic analysis of how the United Kingdom, following Brexit, has repositioned itself as a “rule-shaper” in next-generation technologies by constructing a distinctive model of AI governance. Focusing on the formation and operation of the UK’s governance framework—built upon principles, context sensitivity, and proportionality—this study examines the country’s regulatory philosophy, agile and flexible approaches to standardization, and third-party verification-based AI assurance ecosystem. It traces the policy continuity from the House of Lords Select Committee on Artificial Intelligence (2017–2018) through the National AI Strategy (2021) and the AI Regulation White Paper (2023), and analyzes how institutional mechanisms such as the AI Standards Hub, BSI Flex, and the AI Assurance Roadmap integrate the policy objectives of trust, innovation, and trade. The findings are threefold: (1) The UK complements fragmented regulation and limited enforcement capacity through a principles-based, context-sensitive regulatory design supported by standardization and assurance mechanisms. (2) Standardization functions not only as innovation infrastructure but also as a market trust mechanism, while AI assurance is evolving into a professional service industry that generates a “currency of trust.” (3) Positioned between the EU’s regulatory rigor and the U.S.’s market-driven flexibility, the UK’s hybrid model provides coordination between regulation and innovation, though challenges remain regarding legal enforceability and global interoperability. For Korea, this study offers five policy implications: adopting a principles-based regulatory framework, institutionalizing agile standardization pathways, developing an AI assurance ecosystem, fostering multi-stakeholder governance, and strengthening leadership in global rule-setting.
Authors
- Dong-Hyu Kim (ORCID: https://orcid.org/0000-0003-3702-7218)
- Heejin Park (ORCID: https://orcid.org/0000-0002-8608-5994)
Publication Details
- Journal
- Society for Standards Certification and Safety
- Published
- 2025-09-30
- DOI
- https://doi.org/10.34139/jscs.2025.15.3.79
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00