Artificial intelligence and the transformation of spatial analysis in geography: opportunities, epistemological tensions, and implications for geographical knowledge production in the Global South
Résumé
Introduction This paper examines how artificial intelligence (AI) is transforming spatial analysis in Geography, generating new analytical possibilities whilst producing epistemological tensions for geographical knowledge production, particularly in the Global South. Methods The study employs a qualitative, interpretive design grounded in critical geography, postcolonial theory, and science and technology studies. A systematic literature review and thematic synthesis were conducted. A total of 847 records were retrieved from Scopus, Web of Science, Google Scholar, and ACM Digital Library (2015–2025), of which 52 sources met the inclusion criteria relating to geographic relevance, peer-review status, and full-text accessibility. A PRISMA-compatible screening protocol was applied. Results Findings reveal that AI-enhanced spatial tools, including machine-learning-based remote sensing, predictive geospatial modelling, and large language model-assisted GIS, are expanding Geography's analytical capabilities whilst simultaneously introducing epistemological challenges linked to algorithmic bias, data extractivism, and the re-inscription of colonial spatial imaginaries in computational form. The transformative potential of AI is distributed unevenly, with researchers from the Global South facing structural barriers including data poverty, inadequate infrastructure, and exclusion from foundational AI spatial dataset development, thereby deepening North–South knowledge production asymmetries. Discussion The paper recommends investment in sovereign spatial data infrastructure, AI literacy frameworks for geographical research, and ethical guidelines that foreground the epistemological rights of marginalised communities. It contributes to Geography by theorising the political economy of AI-enabled spatial knowledge production and arguing that critical epistemological vigilance must accompany technical adoption.
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