Harnessing AI for Social Justice and Inclusive Growth

Q: What does a human-centred AI approach mean in the context of India’s development and labour market transformation?

A human-centred AI approach places workers, social justice, and inclusive development at the core of technological advancement. Rather than viewing AI purely as a productivity-enhancing tool, this perspective emphasises how AI can promote decent work, social protection, and shared prosperity. It recognises that technology does not determine outcomes independently; governance frameworks, institutions, and democratic participation shape whether AI widens inequality or fosters inclusion.In India’s context, AI is expected to generate over three million new technology jobs by 2030 while transforming more than 10 million existing roles. Evidence from the International Labour Organization (ILO) suggests that most occupations exposed to generative AI will be transformed rather than replaced. Therefore, the focus must shift to reskilling, worker participation, and social dialogue so that productivity gains translate into improved wages, safety, and working conditions.A human-centred approach thus aligns technological ambition with social purpose. It ensures that AI strengthens trust and dignity at work, reinforcing its role in building socially cohesive and economically resilient societies.

Exploring the potential of artificial intelligence to drive equity, job creation, and social development in India and beyond.

Dhinesh Balasubramanian

•February 19, 2026•6 mins read

Human-centred AI for inclusive growth

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1. Context: AI Transformation and the Question of Social Justice

Artificial Intelligence (AI) is rapidly reshaping economies, labour markets, and governance systems. The central policy question is not whether AI will alter jobs, but whether this transformation will promote social justice, decent work, and shared prosperity.

India hosting the AI Impact Summit in New Delhi — coinciding with the World Day of Social Justice (February 20) — symbolises the intersection between technological ambition and social responsibility. As the first such summit in the Global South, it signals India’s intent to shape AI governance from a development-oriented perspective.

AI’s scale and reach in India make it a significant test case. The country has the world’s largest share of monthly active users of the ChatGPT mobile application and one of the largest user bases for advanced AI platforms.

Technological change is inevitable; its social outcomes are not. Without deliberate governance, AI-driven growth could widen inequalities instead of fostering inclusive development.

“Technological change is not an exogenous force; it is shaped by human decisions.” — Joseph E. Stiglitz

2. Scale of Labour Market Transformation in India

AI is projected to generate substantial employment effects in India over the coming years. By 2030, AI could create over 3 million new technology jobs while reshaping more than 10 million existing jobs.

This indicates that transformation, rather than wholesale job destruction, will characterise AI’s impact. Roles may evolve through task augmentation, automation of routine components, and demand for new skill sets.

India’s labour-intensive economy and large informal sector mean that managing this transition is crucial for social stability and economic inclusion.

Key Projections:

3+ million new AI-related technology jobs by 2030
10+ million existing jobs likely to be reshaped

If workforce adaptation lags behind technological diffusion, structural unemployment and skill mismatches may intensify, undermining demographic dividend gains.

3. Polarised Global Discourse and Governance Imperative

Global debates on AI are increasingly polarised. One strand emphasises productivity gains and innovation; another warns of job losses, inequality, and regulatory gaps.

However, both narratives overlook that outcomes depend on institutional design, regulatory choices, and social dialogue. Technology alone does not determine distributional consequences.

Governance frameworks — inclusive institutions, democratic participation, and worker engagement — are therefore central to shaping AI’s trajectory.

AI governance is fundamentally a question of institutional capacity. Without participatory frameworks, technological gains may concentrate benefits while social costs remain diffused.

“The future depends on what you do today.” — Mahatma Gandhi

4. ILO Evidence: Transformation over Replacement

Evidence from the International Labour Organization (ILO) indicates that AI will primarily transform jobs rather than eliminate them entirely.

Globally, around one in four workers is employed in occupations with some level of exposure to generative AI. However, exposure does not equate to replacement; many roles are likely to be augmented.

To maximise benefits, effective policy frameworks, worker participation, and strong social dialogue are essential. Innovation must be aligned with equitable and inclusive labour outcomes.

Global Exposure Patterns:

25% (approx.) of global workers exposed to generative AI
Greater transformation than displacement expected

Ignoring worker participation in AI integration risks weakening labour standards and eroding trust in technological progress.

5. Digital Platforms and Social Protection: The e-Shram Example

India’s e-Shram platform demonstrates how technology can advance social justice. The platform has enabled registration of over 315 million informal workers for social protection schemes.

With ILO technical collaboration, India’s social protection coverage increased from 19% in 2015 to 64.3% in 2025. This expansion reflects how digital systems can improve welfare targeting and inclusion.

Investments such as Microsoft’s $17.5 billion commitment to AI diffusion aim to integrate AI into e-Shram and the National Career Service portal, enhancing job matching, skill development, and scheme access.

*Outcomes:

315 million+ informal workers registered
Social protection coverage: 19% (2015) → 64.3% (2025)
$17.5 billion private investment supporting AI integration

When AI strengthens public service delivery, it expands inclusion. Without integration into welfare systems, technological progress may bypass vulnerable workers.

6. Institutional Preparedness: National Missions and Budget Measures

India has initiated multiple missions to prepare for the future of work, including:

AI Mission
National Quantum Mission
Anusandhan National Research Fund
Research, Development and Innovation Fund

The Union Budget 2026–27 announced a High-Powered ‘Education to Employment and Enterprise’ Standing Committee to assess AI’s impact on jobs and skills. It will recommend embedding AI education from the school level and promote AI-driven job matching.

These measures reflect an attempt to align education, skilling, and employment systems with emerging technological realities.

Policy Measures:

Institutional assessment of AI’s employment impact
Integration of AI education from school level
AI-based worker-job matching mechanisms

Forward-looking institutional design ensures that AI complements human capital development. Without education reform, skill gaps could widen inequality.

7. Unequal Global Exposure and the Need for Tailored Policies

AI exposure varies significantly across income levels. In low-income countries, only about 11.5% of employment is exposed to generative AI, compared to roughly one-third in high-income economies.

These differences reflect economic structure variations and underscore the need for differentiated policy approaches. One-size-fits-all global governance models may not address diverse labour market realities.

Targeted public investment in digital infrastructure, skills development, and social protection — along with international collaboration — is essential to ensure equitable AI diffusion.

Comparative Exposure:

Low-income countries: 11.5% employment exposure
High-income countries: ~33% employment exposure

Unequal AI exposure can translate into unequal economic gains. Without tailored policies, technological divides may reinforce global inequality.

8. Human-Centred AI and the Value of Work

The convergence of the AI Impact Summit and the World Day of Social Justice underscores that AI must serve workers and societies. Innovation should reinforce dignity, trust, and social cohesion.

Work remains central not only to income but also to identity and social stability. Aligning technological ambition with social purpose is therefore critical.

Human-centred AI governance integrates productivity with protection, innovation with inclusion, and growth with fairness.

If AI development outpaces institutional adaptation, trust deficits may emerge, weakening both economic performance and democratic legitimacy.

“The end of labour is not leisure; it is the chance to engage in more meaningful work.” — John Maynard Keynes

Conclusion

India’s AI trajectory presents both opportunity and responsibility. With large-scale user adoption, significant employment projections, and expanding digital welfare systems, the country stands at a pivotal moment in shaping inclusive AI governance.

Sustained investment in skills, social dialogue, institutional reform, and digital public infrastructure can ensure that AI strengthens productivity while safeguarding dignity and social justice. A human-centred approach will determine whether AI becomes a driver of inclusive development or a source of new inequalities in the world of work.

Quick Q&A

Everything you need to know

A human-centred AI approach places workers, social justice, and inclusive development at the core of technological advancement. Rather than viewing AI purely as a productivity-enhancing tool, this perspective emphasises how AI can promote decent work, social protection, and shared prosperity. It recognises that technology does not determine outcomes independently; governance frameworks, institutions, and democratic participation shape whether AI widens inequality or fosters inclusion.

In India’s context, AI is expected to generate over three million new technology jobs by 2030 while transforming more than 10 million existing roles. Evidence from the International Labour Organization (ILO) suggests that most occupations exposed to generative AI will be transformed rather than replaced. Therefore, the focus must shift to reskilling, worker participation, and social dialogue so that productivity gains translate into improved wages, safety, and working conditions.

A human-centred approach thus aligns technological ambition with social purpose. It ensures that AI strengthens trust and dignity at work, reinforcing its role in building socially cohesive and economically resilient societies.

The global discourse on AI is polarised between optimism about productivity gains and pessimism about job losses. However, both perspectives overlook a key insight: institutional choices determine distributive outcomes. Without appropriate governance, AI could exacerbate inequality, concentrate wealth, and marginalise vulnerable workers. Conversely, inclusive governance can channel AI-driven productivity toward broad-based prosperity.

Mechanisms such as social dialogue between governments, employers, and workers help ensure that policy responses address real workplace concerns. For example, the proposed High-Powered ‘Education to Employment and Enterprise’ Standing Committee in India reflects an effort to anticipate skill shifts and align education systems with emerging technological demands. Embedding AI education from school level onward demonstrates proactive institutional adaptation.

Thus, governance is not a constraint on innovation but a facilitator of equitable outcomes. By strengthening labour standards, investing in digital infrastructure, and fostering democratic participation, India can ensure AI enhances, rather than undermines, social justice.

The e-Shram platform represents a landmark initiative in formalising India’s vast informal workforce. With over 315 million workers registered, it has significantly expanded access to social protection schemes. Supported by technical collaboration with the ILO, India’s social protection coverage increased from 19% in 2015 to 64.3% in 2025.

The integration of AI into platforms like e-Shram and the National Career Service portal has the potential to enhance job matching, skill identification, and targeted delivery of welfare benefits. For example, AI-driven analytics can identify skill gaps, recommend training opportunities, and connect workers to suitable employment opportunities in real time.

This case demonstrates that AI, when aligned with public policy goals, can reduce informality, improve access to entitlements, and strengthen labour market efficiency. It underscores that digital transformation must be embedded within a rights-based framework to maximise inclusive impact.

AI exposure varies significantly across countries and demographic groups. In high-income economies, nearly one-third of employment is exposed to generative AI, compared with only 11.5% in low-income countries. This disparity reflects structural differences in economic composition and digital infrastructure, raising concerns about a widening global digital divide.

Within countries, inequalities also persist across gender, age, and socio-economic categories. Workers lacking digital skills risk exclusion from AI-enhanced labour markets. If public investment in digital literacy and infrastructure remains inadequate, AI may reinforce existing hierarchies rather than dismantle them.

Addressing these challenges requires targeted public investment in skills development, affordable digital access, and robust social protection. International collaboration and solidarity are equally vital to prevent technological concentration in a few economies. Without such interventions, AI’s transformative promise could deepen structural inequalities instead of promoting inclusive growth.

An effective AI strategy must integrate innovation with equity. First, invest in education and skilling, embedding AI literacy from school level and providing mid-career reskilling programmes. The Education to Employment and Enterprise Standing Committee can guide curriculum reforms aligned with emerging job profiles.

Second, strengthen digital public infrastructure to ensure universal access. Platforms like e-Shram and AI-enabled job portals should prioritise inclusivity, transparency, and data privacy. Incentivising private investment—such as Microsoft’s AI diffusion commitment—should be tied to measurable social impact outcomes.

Third, institutionalise social dialogue mechanisms involving workers’ representatives in AI deployment decisions. This ensures technological adoption enhances workplace safety and productivity without eroding labour rights. By combining forward-looking innovation policies with inclusive governance, India can position itself as a model for the Global South in building a socially just, AI-driven economy.