AI-driven urban futures from global trends to African perspectives

Purpose Despite rapid advances in Artificial Intelligence (AI), and specifically Generative Artificial Intelligence (GenAI) for urban planning, a gap persists between these innovations and their applicability in African contexts shaped by informality, data scarcity, limited capacity and climate vulnerability. This study examines how GenAI is reshaping urban planning globally and assesses its relevance, adaptability and risks in African contexts, identifying pathways for inclusive, legitimate and context-sensitive deployment. Design/methodology/approach A systematic literature review used a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided framework extended through PRALSMA (Preferred Reporting of AI-integrated Literature Search and Meta-Analysis), a reporting extension for transparent AI-assisted reviews. Peer-reviewed articles (2020–2025) from Web of Science and OpenAlex, with selected grey literature, gave 82 sources analysed through manual review and AI-assisted tools, with all outputs verified and triangulated for robustness and traceability. Findings GenAI is transforming urban planning through multimodal workflows enabling rapid scenario generation, visualisation and communication, but effectiveness depends on localisation, bias mitigation, institutional capacity and legitimacy. Without these, GenAI risks misleading or exclusionary “blueprint” solutions, underscoring the need for context-sensitive adaptation. Originality/value The study integrates creativity-in-design, relational agency and democratic design to frame GenAI as a socio-technical participant rather than an autonomous planner, offering an Africa-relevant agenda for responsible, human-centred implementation aligned with equity, sustainability and resilience.