AI Governance and User Trust in E-Government: A Comparative Study of the United Kingdom and Saudi Arabia

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As governments expand artificial intelligence (AI) in public services, user trust may depend on the governance safeguards surrounding its deployment. This study examines the association between national AI governance arrangements and user trust in e-government platforms in the United Kingdom and Saudi Arabia. A comparative mixed-methods design combined documentary analysis across 16 governance dimensions with a cross-sectional survey of 100 GOV.UK and Absher users (50 per platform). Trust was measured using an adapted 12-item trust-in-automation checklist. Absher users reported higher overall trust than GOV.UK users, t(98) = 3.30, p = .001, Cohen’s d = .66 (95% CI [.26, 1.06]). The difference was concentrated in the study-defined integrity-related dimension, while the ability-related composite did not differ significantly. A direct integrity-minus-ability contrast confirmed that the between-group difference was greater for integrity-related perceptions, t(98) = 5.27, p < .001, d = 1.05. Although the United Kingdom ranked higher on the 2025 Government AI Readiness Index, this was not accompanied by higher user trust in the platform examined. The findings are consistent with structural assurance as a possible interpretive mechanism, while not establishing causation. These findings should be interpreted in light of the modest sample size and adapted measurement approach. The study proposes a five-component framework centred on binding transparency, accessibility compliance, clearly assigned accountability, enforcement visibility, and continuous trust monitoring, and provides an initial cross-national benchmark for examining user trust under contrasting AI governance environments.