AGENTIC INTELLIGENCE FOR SMART CITIES AND SOCIETY

Abstract

Agentic intelligence — the deployment of autonomous, goal-directed artificial intelligence systems capable of perceiving urban environments, reasoning across complex datasets, and executing consequential actions with minimal or no human intervention — represents the most transformative frontier in contemporary smart city development, encompassing a rapidly expanding ecosystem of technologies and governance challenges whose combined scope will define the trajectory of urban civilisation over the coming decades. This chapter provides a comprehensive and rigorous scholarly analysis of the role of agentic AI systems in smart city and societal transformation, examining the theoretical foundations, principal application domains, governance architectures, implementation methodologies, and critical challenges that characterise the deployment of autonomous intelligence across urban infrastructure, public services, and civic governance. Drawing upon a synthesis of empirical research, policy documentation, and primary case study evidence spanning 2018 through 2026, the analysis demonstrates that agentic AI systems are already delivering measurable improvements in urban operational efficiency, resource allocation optimisation, public safety enhancement, and citizen service quality across transportation networks, energy grids, healthcare delivery systems, and environmental monitoring programmes in cities worldwide. Four original case studies — examining AI-driven mobility management in Singapore, smart energy optimisation in Barcelona, autonomous public safety systems in Dubai, and citizen-centric governance AI in Tallinn — illuminate the practical architecture, governance requirements, and societal implications of large-scale agentic AI deployments across diverse urban and institutional contexts. The chapter identifies six principal challenge categories — data privacy and security, the digital divide, interoperability deficits, governance and accountability frameworks, infrastructure financing, and algorithmic bias — and examines the technical architectures, regulatory instruments, and institutional mechanisms that leading cities have developed to address each. The analysis concludes by mapping the frontier research and policy directions, including autonomous city operating systems, AI-mediated participatory governance, and adaptive urban intelligence networks, that will define smart city development over the next decade as agentic AI capabilities advance and urban populations continue their historically unprecedented growth.