Localizing AI in Rural India: The Role of Talent Management in Reconfiguring Agricultural Knowledge Systems

As artificial intelligence (AI) is increasingly integrated into agriculture-focused development agendas, its use in rural field settings challenges current thinking about fit, equity, and sustainability. This paper examines the overlooked dimensions of how talent management processes impact the sociotechnical localization of AI in rural agricultural ecosystems in India. Based on multi-sited qualitative case studies in Karnataka, Bihar, and Maharashtra, we explore how talent pipelines, including agri-digital intermediaries, AI translators, and local facilitators, mediate the adoption, translation, and incorporation of AI tools by small institutional and professional farmers. The findings suggest that human infrastructure is not merely supportive but constitutive of the successful integration of AI, especially in settings characterized by educational asymmetries, caste hierarchies, and gendered exclusions. Informed by sociotechnical systems theory and the concepts of knowledge coproduction and epistemic justice, this research contends that talent management must be reimagined as a fundamental infrastructural and ethical spine for digital innovation. The analysis conceptualizes AI localization as a negotiated alignment between algorithmic systems and agrarian lifeworlds made possible by contextually embedded, culturally literate, and institutionally embedded human agents. This helps push the boundaries of what it means for AI to be technically feasible, socially situated, and democratically transformed in the Global South.