AI, Jobs, and the Social Contract

Executive summary

Executive summary

“AI will reorganise work at scale. How it reorganises opportunity, and in whose interest, is a matter of governance.”

Artificial intelligence is accelerating structural change across labour markets. But the current trajectory reveals something beyond a technology story: economic and decision-making power over AI deployment is concentrated in fewer than ten firms, while democratic oversight over how benefits and costs are distributed remains limited and uneven.

AI-driven disruption is not technologically predetermined but shaped by policy and institutional choices. Despite unprecedented investment, aggregate productivity gains remain modest, concentrated among a narrow set of frontier firms, and largely decoupled from wage growth or employment expansion. At the same time, disruption is already spreading across white-collar, blue-collar, and informal work simultaneously. Entry-level pathways are narrowing, organisational middles are thinning, and algorithmic management is reshaping work even where jobs persist. Women are disproportionately exposed, concentrated in early-automated roles, and their income loss carries macroeconomic consequences by suppressing household demand in economies that depend on it.

In labour-surplus democracies such as India, unmanaged automation risks compressing wages, weakening domestic demand, squandering the demographic dividend, and eroding the social contract. The question is not whether to adopt AI, but how to govern its adoption and in whose interest.

This brief advances seven principles for democratic management of the transition: democratic participation in deployment decisions; transparency and accountability for labour and data impacts; income security and structured pathways during transition; shared prosperity through fair distribution of productivity gains; data and knowledge justice; investment in domestic productive capacity; and international accountability for transnational AI firms.

These principles are translated into a sequenced action framework. Immediate steps include a national White Paper on AI and Work, early-warning labour observatories, and mandatory AI–Labour Impact Reports for large employers. Medium-term measures focus on parliamentary oversight, coordinated transition missions, and substantive reform of skilling systems. Structural reforms include building indigenous AI capability, embedding employment conditions in public procurement, and advancing global coordination on labour standards and data compensation.

For India and the broader Global South, the stakes are acute. With the world’s largest youth populations and service-led growth models, these economies have the most to lose from unmanaged automation and the most to gain from governing it well. The benefits of AI will depend on whether democratic states can shape adoption to expand opportunity across the middle of the labour market, not merely concentrate returns at the top.

AI will reorganise work at scale. How it reorganises opportunity, and in whose interest, is a matter of governance.

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