Artificial Intelligence as an Equalizer or Divider in India: Digital Public Infrastructure, Human Capital, and Inclusive Technology Adoption

India offers a distinctive setting for examining whether artificial intelligence (AI) can broaden economic opportunity or reinforce pre-existing inequality. The country combines population-scale digital public infrastructure, a rapidly expanding technology and startup ecosystem, large regional and socio-economic disparities, and a workforce in which informal employment remains dominant. This article develops a secondary empirical synthesis of evidence on inequality, digital infrastructure, AI adoption, financial inclusion, labor-market transition, entrepreneurship, and human-capital readiness. It integrates national and international datasets and policy reports with sectoral evidence from finance, public-language infrastructure, education and skills, and technology services. The analysis distinguishes between equalizing mechanisms—lower transaction costs, alternative credit assessment, multilingual access, scalable learning, and distributed entrepreneurship—and dividing mechanisms, including capital-biased productivity gains, uneven compute access, algorithmic exclusion, regional concentration, and skill-premium effects. The central finding is that AI is not intrinsically redistributive. Its distributional effect depends on an institutional complementarity among universal digital access, AI-relevant human capital, inclusive entrepreneurship, responsible governance, and mechanisms that allow workers and small firms to capture productivity gains. The paper proposes an Inclusive AI Capability framework and argues that education systems are a critical transmission mechanism between technological adoption and equitable participation. India’s experience therefore provides a useful model for emerging economies: AI can support inclusive growth, but only when technology policy is integrated with education, skills, public digital infrastructure, and social protection rather than treated as a stand-alone innovation agenda.