Assuming that Artificial Intelligence (AI) is changing the approach to urban planning issues, this study investigates whether changes will start to occur at a theoretical level or if technological innovations will mostly be endured rather than used with full knowledge. The authors observed that technological innovation often occurs without a unifying theoretical framework to provide knowledge and a basis for its adoption. The first use of technology in urban management dates to the late 1950s, and it has recently regained attention within the scientific literature; however, a significant deficiency still exists regarding the definition of a theoretical framework for its use. Focusing on the use of AI in urban and regional planning, this study aims to address this gap by outlining theoretical observations that can guide the integration of AI into new approaches for the management of urban transformations. The enormous impact that the rapid and pervasive spread of AI is having on all human activities necessitates the definition of new educational and disciplinary processes, especially in fields like urban planning, which rely on the high potential of such technology for envisioning future scenarios. It is therefore essential to assume that AI will also modify the management of urban and territorial transformations. This study aims to suggest a framework for scholarly debate on the need to define new historical–disciplinary dimensions by appropriately using AI in the phases of urban planning, avoiding the risk of passively accepting AI’s potential by delegating the development of urban planning tools to artificial reasoning. Building on these premises, this study first provides a thorough and critical literature review regarding the use of AI in urban planning and then proposes a methodological framework. The final section discusses the possibilities and limitations of this approach, thereby contributing to the scientific debate on defining a theoretical framework for the adoption of AI within urban and regional planning processes.
Fistola et al. (Wed,) studied this question.