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

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Authors: Abdulkarim K. Alhowaish
Cited by: 2

Abstract

The integration of artificial intelligence (AI) into urban governance has become a defining feature of contemporary smart city strategies. While AI is increasingly promoted as a tool for enhancing efficiency and data-driven decision-making, its role in participatory urban planning remains insufficiently understood, particularly in rapidly urbanizing metropolitan contexts. This study investigates how AI can support participatory urban planning for sustainable smart cities, emphasizing the mediating role of institutional capacity and the reinforcing role of public trust. Using a mixed-methods research design, the study combines a stakeholder survey (n = 260) with thematic analysis of open-ended responses to investigate perceptions of AI awareness and use, participation quality, institutional and technical readiness, and trust-related dynamics in the Dammam Metropolitan Area, Saudi Arabia. The findings reveal a persistent participation paradox of relatively high AI awareness and digital readiness coexisting with low perceived influence, limited outcome effectiveness, and weak trust in participatory processes. Institutional fragmentation, skill gaps, and regulatory ambiguity emerge as key constraints limiting the participatory impact of AI, with stakeholders favoring AI tools that enhance transparency, deliberation, and accountability rather than automation. Qualitative insights indicate that AI is perceived less as a standalone technological solution and more as a catalyst for broader institutional reform, capacity building, and sustainability-oriented service improvement. The study contributes to urban science and smart city scholarship by empirically validating a governance-centered conceptual framework that positions AI as a facilitative technology embedded within institutional arrangements. The findings offer policy-relevant insights for cities seeking to align AI-driven innovation with inclusive, trust-oriented, and sustainable urban planning.

Fields of Study & Subjects

Smart Cities and Technologies E-Government and Public Services Human Mobility and Location-Based Analysis

Publication details

Journal / source
Preprints.org
Publisher
MDPI AG
Publication date
3 February 2026
Document type
Preprint