A Comparative Analysis of AI Governance in the United Kingdom and the United Arab Emirates: The Role of Regime Type
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Date
2025
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Publisher
Saudi Digital Library
Abstract
This dissertation probes the reasons why national AI governance frameworks diverge despite
sharing a shared global vocabulary of principles. It contrasts the United Kingdom (UK) and the
United Arab Emirates (UAE) two high-income, AI-aspiring regimes that differ immensely in regime
type. The core hypothesis is that regime type is a first-order determinant of governance
architecture: democracies, grounded in consent and horizontal accountability, will implement
enforceable checks on ethics, accountability, and transparency; competitive-authoritarian
regimes, grounded in vertical control and performance, will accumulate power and leverage AI
to augment state capacity with limited external competition. Political economy, bureaucratic
traditions, and norm diffusion are salient but only operate through regime incentives.
The study makes use of qualitative content analysis of official policy texts (22 UK, 16 UAE; 2017–
2025) through an agreed codebook for four outcome dimensions: Ethics, Accountability,
Openness, and Control and three competitor-explanation tracers economic structure,
institutional configuration, and international norms. Ethics/accountability/openness in the UK
corpus account for around 48% of coded material and are associated with concrete instruments
(transparency recording standards, regulator audit powers, avenues to redress). In the UAE
corpus, central steering and state-led deployment and security/public safety uses are high, with
ethics language present but more programmatic and vertically accountable.
The regime-type hypothesis (H1) is supported by evidence, and conditional, mediating effects are
found for economic structure (H2), bureaucratic politics (H3), and norm diffusion (H4). The
dissertation presents a mechanism-rich explanation of AI governance variation, a portable four dimension coding system, and regime-specific policy advice (e.g., converting advice into
responsibilities and redress in democracies; externalising audit hooks and disclosure baselines in
centralised regimes). It concludes by articulating scope conditions and an agenda for scaling the
design to additional cases, sectors, and longitudinal evidence of implementation
Description
Artificial intelligence (AI) has moved from the periphery of business and science to the center of
national strategy. Governments commission AI strategies, fund safety research centers, hold
international summits, and enact rules for public-sector use. But underlying a striking worldwide
convergence in language: "reliable," "people-first," "just," "transparent" are broadly different
designs for control. This dissertation addresses that difference through a structured comparison
of two trailblazing, ambitious AI states: the UK and the UAE.
Both governments openly aim to be the world leaders in AI and have heavily invested in research,
digital infrastructure, and public sector adoption. Both favor international norms and host
cooperation forums. They diverge, however, in their choices: the UK values regulator-led control,
transparency obligations, and mechanisms of redress; the UAE values central orchestration, rapid
deployment in government services and safety/security use cases, and internal (vertical)
accountability.
Keywords
Political, Traditions, IA, Relations
Citation
AlSaud , 2025, A Comparative Analysis of AI Governance in the United Kingdom and the United Arab Emirates: The Role of Regime Type