AI-Assisted Inclusive Architecture and Neighbourhood Planning in Emerging Nigerian Cities Through Human-in-the-Loop Frameworks

Emerging Nigerian cities are expanding through formal estates, peripheral subdivisions, informal neighbourhoods and road-led corridors that can separate households from jobs, schools, healthcare, affordable transport and usable public space. This critical structured narrative review examines how AI-assisted and related computational methods can support inclusive architectural design and neighbourhood planning through an explicitly architecture-planning lens, while distinguishing AI-specific methods from conventional GIS, network analysis and scenario modelling. The evidence base comprises 48 substantive peer-reviewed journal articles, two peer-reviewed review-methodology papers and 15 institutional, statutory and policy documents. The synthesis indicates that AI-specific methods can augment prediction, classification, clustering and pattern recognition. In contrast, GIS, network analysis and scenario modelling provide complementary support for accessibility mapping, service-gap diagnosis, housing-location assessment and mobility analysis. Their usefulness depends on representative data, local validation, community knowledge and professional interpretation. The proposed framework centres on urban and regional planning and architecture as complementary professional lenses while recognising additional transport, infrastructure, accessibility, community-engagement and data/AI expertise where required. An iterative human-in-the-loop framework links inclusive data and community knowledge to digital/GIS and AI-assisted analytics, planning interpretation, architectural design translation, joint validation, neighbourhood monitoring and feedback, under cross-cutting governance safeguards. The framework proposes that digital and AI-assisted interventions be evaluated through disaggregated indicators of accessibility, spatial quality, housing inclusion and liveability rather than technological novelty alone.