Characterised as the Fourth Industrial Revolution, AI is envisioned to reshape urban socio-technical interactions and drive solutions to the world’s ‘grand challenges.’ Despite this foresight, there is an absence of qualitative studies that critically engage with the intersection between AI, sustainable development, cities, and the Global South. This represents an urgent research gap due to the synonymity of ‘digitalisation-as�urbanisation’ in the Global South, the acceleration of urban AI deployment, and the international pursuit of the SDGs. Through primary interviews with scholars and corporate AI technologists and secondary case study research, this thesis addresses the question of AI’s impact on urban inclusion and urban environmental sustainability. Based on primary, qualitative data analysis, this paper’s thematic data map establishes the key determinants of AI’s impact on sustainable urban development in the Global South as follows: Access, Representation, Privacy, Experimentation vs Regulation, Agency and Efficiency. These primary findings were then mobilised to analyse secondary case studies of urban AI deployment for security, urban planning, citizen services, 2 and DRM across Global South cities (e.g. Johannesburg, Hyderabad, and Buenos Aires). In terms of urban inclusion, this paper concludes that AI in its current form risks the exacerbation of pre�existing social injustices due to data and infrastructural inequity and unethical surveillance practices that impacts urban service provision and spatial access. In terms of urban environmental sustainability, this paper argues that AI’s capacity for innovative urban climate action will only be sustainable if its carbon and water footprint is proactively addressed and the digital divide is bridged.

Characterised as the Fourth Industrial Revolution, AI is envisioned to reshape urban socio-technical interactions and drive solutions to the world’s ‘grand challenges.’ Despite this foresight, there is an absence of qualitative studies that critically engage with the intersection between AI, sustainable development, cities, and the Global South. This represents an urgent research gap due to the synonymity of ‘digitalisation-asurbanisation’ in the Global South, the acceleration of urban AI deployment, and the international pursuit of the SDGs. Through primary interviews with scholars and corporate AI technologists and secondary case study research, this thesis addresses the question of AI’s impact on urban inclusion and urban environmental sustainability. Based on primary, qualitative data analysis, this paper’s thematic data map establishes the key determinants of AI’s impact on sustainable urban development in the Global South as follows: Access, Representation, Privacy, Experimentation vs Regulation, Agency and Efficiency. These primary findings were then mobilised to analyse secondary case studies of urban AI deployment for security, urban planning, citizen services, 2 and DRM across Global South cities (e.g. Johannesburg, Hyderabad, and Buenos Aires). In terms of urban inclusion, this paper concludes that AI in its current form risks the exacerbation of preexisting social injustices due to data and infrastructural inequity and unethical surveillance practices that impacts urban service provision and spatial access. In terms of urban environmental sustainability, this paper argues that AI’s capacity for innovative urban climate action will only be sustainable if its carbon and water footprint is proactively addressed and the digital divide is bridged.