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

Myra Agarwal, Trasha Gupta · Zenodo (CERN European Organization for Nuclear Research) · 7 Oct 2026

Where this sits in the debate

Will AI widen inequality? · its finding: it depends (why studies differ)

Direction of the finding as read from the abstract by an AI model (AI-written).

Key takeaway AI-written

A secondary synthesis of data and policy reports asks whether AI will narrow or widen inequality in India. It contrasts equalising mechanisms such as lower transaction costs and multilingual access with dividing ones such as capital-biased gains and uneven compute access, concluding that the distributional outcome depends on institutions rather than the technology itself.

The paper in three steps AI-written

Written by an AI agent from the paper's abstract, which is the primary source and is quoted below.

The question

Will AI broaden economic opportunity in India or deepen existing inequality?

The approach

A secondary synthesis of national and international datasets and policy reports on digital infrastructure, AI adoption, financial inclusion, labor-market transition, entrepreneurship and skills in India.

The findings

AI's distributional effect is not built in: it depends on universal digital access, AI-relevant skills, inclusive entrepreneurship, governance and ways for workers and small firms to capture productivity gains. The paper proposes an Inclusive AI Capability framework.

How to read it: review. A synthesis of existing studies — breadth over novelty; quality depends on what it includes and excludes.

Limitations and counterpoints AI-written

Based on existing data and reports, with no new causal estimates of AI's effect on inequality.

Abstract

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.

About this publication

Preprint. A preprint — posted publicly before or without journal peer review; findings may still be revised.

Published: 2026 (recently)
Citations: 0 (OpenAlex)