AI Governance, Urban Sustainability Transitions, and the Institutional Determinants of Smart City Transformation: A Comparative Cross-City Framework

This paper advances a governance-centred framework for understanding how artificial intelligence contributes to urban sustainability transitions. Drawing on systematic thematic analysis of 250 policy documents across five global cities—Singapore, Amsterdam, Barcelona, Seoul, and Toronto—the paper argues that AI contributes to sustainable outcomes primarily by transforming governance structures rather than through technical optimisation alone. The paper identifies four institutional conditions that determine whether the sustainability dividend of AI deployment is realised: regulatory coherence, multi-stakeholder participation, transparency and auditability of algorithmic decision-making, and adaptive governance capacity. A comparative framework is developed to assess AI governance maturity across urban sustainability domains, including energy management, climate adaptation, mobility, and green public procurement. The paper further examines AI-blockchain integration for climate-responsive governance, drawing on the South Tyrol and Estonia cases as examples of distributed ledger technologies providing the audit trail guarantees that AI systems structurally lack. Findings suggest that governance design—not AI capability—is the primary determinant of sustainable transformation outcomes. The paper contributes to the emerging interdisciplinary literature at the intersection of AI governance, smart city development, and organisational sustainability, offering a practitioner-relevant framework for policymakers, city managers, and business leaders engaged in AI-enabled green transformation.