Conceptualising the emergence of Agentic Urban AI: from automation to agency
Alok Tiwari
Abstract
Abstract Contemporary urban systems are evolving under the influence of artificial intelligence (AI), advancing beyond automation into autonomous agency. Traditional smart city technologies have focused on operational efficiency through human-directed automation, but this study explores the rise of Agentic AI, AI systems capable of independently formulating and pursuing urban objectives. Urban sensing, enhanced by large language models, enables dynamic goal-setting and strategic adaptation, key to this agency. Employing a conceptual-methodological approach, the research integrates insights from Urban Studies, AI theory, and governance scholarship. Through critical literature review, conceptual mapping, and empirical analysis of platforms such as Alibaba’s City Brain and Citymind AI Agent. It identifies early agency indicators, such as goal reprioritisation, and proposes a typology distinguishing automation, autonomy, and agency. These findings suggest AI-driven urban ecosystems with partial decision-making autonomy, compelling a transformative shift in governance. This evolution demands a reassessment of regulatory, ethical, and planning frameworks, to ensure equitable and sustainable AI integration in urban environments via participatory governance and proactive regulation.