Governing Public-Sector AI: A Comparative Study of Saudi Arabia and the United Kingdom
| dc.contributor.advisor | Vasiliki, Koukoulioti | |
| dc.contributor.author | AlKhatib, Kanit | |
| dc.date.accessioned | 2026-05-17T09:49:43Z | |
| dc.date.issued | 2026 | |
| dc.description | The overarching aim of this dissertation is to analyze and compare the regulatory frameworks that govern AI in Saudi Arabia and the United Kingdom specifically in public-sector decision-making. It also attempts to evaluate the functional strengths and weaknesses of each model as tools for managing AI-related risks while enabling innovation. The central research question is: How do Saudi Arabia and the United Kingdom regulate the design and deployment of artificial intelligence in public-sector decision-making, and what do their respective approaches reveal about the possibilities and limits of harmonizing AI governance across different legal and political systems? In order to answer this question in a structured way, the dissertation asks a series of sub-questions: 1. Legal architecture for public-sector AI How is responsibility for governing public-sector uses of AI allocated among institutions in Saudi Arabia and the UK, and what are the main sources of legal authority that apply when public bodies design, procure or deploy AI systems? 2. Risk and safety in government decision-making How does each jurisdiction conceptualise and manage AI-related risks in public-sector decision- making? These include safety, security and human rights impacts. 3. Data governance How do the Saudi Personal Data Protection Law and the UK’s data protection regime structure the use of personal data in public-sector AI systems, particularly for profiling and automated decision-making? 4. Accountability, transparency, and remedies What mechanisms exist in each jurisdiction to ensure transparency, explainability and contestability of AI-assisted public decisions, and what forms of administrative or judicial oversight are available where individuals are harmfully affected? 5. Harmonisation How far do global AI governance initiatives and soft-law instruments shape public-sector AI in Saudi Arabia and the UK, and where do the differences in legal culture, political structure and administrative traditions lead to different regulatory choices? | |
| dc.description.abstract | Artificial intelligence (AI) has moved from a largely technical domain to the centre of global legal and policy debates . Today, AI systems include search engines, recommendation systems, and an emerging class of generative and “frontier” models that can produce text, code, images, and other content at scale. These systems create opportunities for economic growth, efficiency, and public- sector innovation, but they also give rise to complex risks for safety, fundamental rights, and security. This dissertation focuses specifically on the use of AI by government and public-sector bodies rather than attempting to cover all private-sector applications. States and international organisations have begun to develop principles and legal frameworks to govern these risks under the banner of “trustworthy” or “responsible” AI. Saudi Arabia and the United Kingdom occupy distinctive positions within this emerging global landscape. Saudi Arabia has framed AI as a core enabler of its Vision 2030 economic diversification agenda and has created a centralized institutional structure through the Saudi Data and Artificial Intelligence Authority (SDAIA), supported by the National Data Management Office (NDMO) and other digital regulators. The National Strategy for Data and AI (NSDAI) sets ambitious targets for AI-driven growth and capacity building. Moreover, SDAIA has adopted national AI ethics principles and guidance intended to shape both public and private sector deployment . By contrast, the UK has presented itself as a global leader in “pro-innovation” AI governance. The 2021 National AI Strategy and the 2023 White Paper “A pro-innovation approach to AI regulation” articulate a model that avoids a single comprehensive AI statute and instead relies on existing regulators applying a common set of AI principles within their respective mandates. The establishment of a dedicated AI safety body, the AI Security Institute, signals an increasing focus on advanced AI safety and international cooperation, even in the absence of a full AI Act . Both jurisdictions seek to be AI leaders through different institutional designs and regulatory techniques. This dissertation uses these differences to examine how states can pursue innovation while managing the risks and societal impacts of AI. | |
| dc.format.extent | 25 | |
| dc.identifier.citation | Oscola | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14154/79009 | |
| dc.language.iso | en | |
| dc.publisher | Saudi Digital Library | |
| dc.subject | Comparative study | |
| dc.subject | AI regulation | |
| dc.title | Governing Public-Sector AI: A Comparative Study of Saudi Arabia and the United Kingdom | |
| dc.type | Thesis | |
| sdl.degree.department | Law Department | |
| sdl.degree.discipline | Law | |
| sdl.degree.grantor | Queen Mary Univesity | |
| sdl.degree.name | LLM Corporate and Commercial |