Sustainable and Inclusive AI Governance in Municipal Self-Service Systems: Ethical, Smart-Government, and Generative AI Perspectives

As municipalities increasingly adopt artificial intelligence (AI) and generative AI (GenAI) to automate self-service technologies (SSTs), concerns related to fairness, transparency, accountability, and citizen trust have become central to sustainable public-sector governance. While existing studies emphasize either AI adoption or high-level ethical principles, limited empirical research explains how governance mechanisms translate into user-level outcomes in municipal services, particularly in the context of emerging GenAI capabilities. This study addresses this gap by examining how governance antecedents and system design attributes shape user satisfaction, trust, and perceived fairness in AI-enabled municipal SSTs in the United Arab Emirates (UAE). A mixed-methods research design was employed, combining a comparative analysis of international and UAE AI governance frameworks with semi-structured interviews ( n = 16) and a survey of municipal employees and service users ( n = 272). Qualitative findings reveal persistent concerns regarding data privacy, fairness, explainability, and the absence of standardized municipal-level accountability instruments. Quantitative analysis shows that perceived helpfulness significantly increases user satisfaction, while perceived fairness strongly predicts continued usage intentions. In contrast, system responsiveness exhibits a negative association with satisfaction, highlighting an expectation–performance gap in automated service delivery. Based on these findings, the study proposes a governance–implementation–outcomes model that operationalizes ethical AI principles into measurable governance and service-design mechanisms. Unlike prior adoption-focused or purely normative frameworks, this model empirically links governance instrumentation to citizen-centered outcomes, offering practical guidance for inclusive and sustainable AI and GenAI deployment in municipal self-service systems. The findings contribute to debates on sustainable digital governance by demonstrating how ethically governed AI systems can reinforce public trust, service equity, and long-term institutional resilience.