Artificial intelligence could deliver a major productivity boost across industries, but the transition could also widen the gap between economic output and workers’ wages unless governments and businesses move quickly on skills and social protection.
A recent analysis cited by IANS draws parallels between the current AI wave and earlier industrial revolutions, warning of a period in which productivity and corporate wealth could rise faster than wages and living standards. The phenomenon has been described by economic historians as an “Engels’ Pause”.
For India, the employment challenge could be particularly significant. Labour-intensive sectors such as IT outsourcing, business process management and customer support have been important sources of employment, but AI systems are increasingly capable of handling tasks such as basic coding, data entry, customer assistance and document processing.
At the same time, technology-led disruption has historically created new categories of employment. The industrial revolution generated factory work, the automobile era built large manufacturing and services ecosystems, while the digital economy created software, e-commerce and platform-based jobs. AI could similarly create roles and industries that are difficult to anticipate today.
The transition, however, is unlikely to be uniform. PwC’s 2026 AI Jobs Barometer found that skills requirements in the most AI-exposed jobs are changing more than twice as quickly as in less-exposed roles. It also found that AI-exposed entry-level jobs are increasingly demanding skills traditionally associated with more senior positions, including leadership and judgement.
This puts reskilling at the centre of the employment debate. Policymakers will need to expand digital education and continuous learning, while universities and vocational institutions may have to adapt curricula more rapidly to changing demand. Employers, meanwhile, will need to rethink how they redeploy workers whose routine tasks are increasingly automated.
For India, the stakes are particularly high given the size of its young workforce and technology sector. A NITI Aayog report has estimated that AI could potentially lead to the loss of 1.5 million technology jobs by 2031 or create up to four million new opportunities, depending on how the transition is managed.
The emerging consensus is therefore less about resisting AI than determining who benefits from its productivity gains. For businesses, that means treating AI adoption alongside workforce planning and skills development. For policymakers, it means preparing for labour-market disruption before displacement becomes a wider social and economic problem.
The real test of the AI economy may ultimately be whether higher productivity translates into more productive workers and better jobs, rather than simply fewer people doing more work.