AI Governance and User Trust in E-Government: A Comparative Study of the United Kingdom and Saudi Arabia
Mohamed Benaida, Fayçal Hamdi, Mahmud Mansour, Ahmad B. Alkhodre, Abdullah Alshanqiti, Tanweer AlamAs governments expand artificial intelligence (AI) in public services, user trust may depend on the governance safeguards surrounding its deployment. This exploratory study combines a documentary analysis of 16 AI governance dimensions in the United Kingdom and Saudi Arabia with a survey of 100 GOV.UK and Absher users recruited through non-probability sampling (50 per group). The documentary comparison identifies contrasting governance arrangements, with a more distributed, sector-led approach in the United Kingdom and more centralised coordination in Saudi Arabia. Using an adapted 12-item trust questionnaire, surveyed Absher users reported higher average scores than surveyed GOV.UK users (3.47 versus 3.29), with the largest item-level differences concerning suspiciousness, wariness, and perceived integrity. Given limited internal consistency and unestablished English–Arabic measurement equivalence, these differences are interpreted as exploratory item-score patterns. Respondents’ awareness of national AI governance arrangements was not assessed, so structural assurance is discussed as a theoretical lens rather than a tested explanation. The study contributes a structured governance comparison, descriptive evidence of trust-item patterns in two selected platform-user groups, and a five-component framework addressing transparency, accessibility, accountability, enforcement visibility, and continuous trust monitoring.