Al-Enabled Participatory Urban Planning for Sustainable Smart Cities: Evidence from the Dammam Metropolitan Area, Saudi Arabia

Artificial intelligence (AI) is increasingly embedded in smart city strategies, yet its role in advancing participatory urban planning remains underexamined, particularly in rapidly urbanizing metropolitan contexts of the Global South. This exploratory, governance-centered study investigates how AI can support participatory urban planning for sustainable smart cities, emphasizing institutional mediation and trust dynamics. Using a convergent mixed-methods design, the research combines a purposive stakeholder survey (n = 260) with qualitative thematic analysis to assess AI awareness and use, participation quality, institutional and technical readiness, and public trust in the Dammam Metropolitan Area, Saudi Arabia. The findings reveal a participation paradox: relatively high AI awareness and digital readiness coexist with low perceived influence and limited confidence in participatory outcomes. Institutional coordination gaps, skill constraints, and regulatory ambiguity mediate the translation of AI adoption into meaningful engagement. Stakeholders favor AI applications, such as interactive mapping, predictive analytics, and digital twin visualization, that enhance transparency and deliberation over automated decision systems. Qualitative evidence further indicates that AI is perceived not as a standalone solution, but as a catalyst for institutional reform, capacity development, and sustainability-oriented governance. The study contributes to urban science by empirically validating a socio-technical framework that positions AI as a facilitative governance instrument embedded within institutional and trust-building processes. The findings offer policy-relevant insights for cities seeking to align AI-driven innovation with inclusive, accountable, and sustainable urban development.