Despite a strong push towards artificial intelligence, in the Economic Survey 2025–26, the government has acknowledged that while rapid AI adoption can raise productivity and output, it also increases the risk of job displacement if not carefully sequenced.
The survey found that AI raises the marginal productivity of capital relative to labour, particularly in white-collar service sectors where many tasks are routine and easily codified. “Firms driven by cost reductions and maximising productivity gains are more inclined to rapidly scale up AI adoption, increasing the likelihood of capital-labour substitution in specific task categories. Most of these tasks are concentrated in low-value-added segments of the service sector, and high exposure to AI means firm leadership may view these jobs as redundant,” the survey warned.
This trend creates a structural tension for India. Faster AI adoption can strengthen competitiveness and lift aggregate productivity, but uncalibrated deployment risks displacing workers faster than the economy can absorb them, weakening employment generation in a labour-surplus context.
Rather than advocating a slowdown in AI adoption, the survey stressed that the key policy challenge lies in pacing its diffusion so that labour augmentation precedes labour substitution. It noted that the labour-market impact of new technologies is not predetermined, but shaped by how skills, tasks and institutions evolve together.
The survey also flagged India’s shortage of advanced, experience-driven AI talent as a major constraint. To address this, it called for attracting experienced practitioners—particularly through diaspora return pathways—and embedding industry experts within academic institutions through fellowships, lateral entry and apprenticeship models.
“In this context, depth of domain knowledge becomes a binding constraint, as AI can access vast troves of information but lacks an internal sense of context or salience,” it noted. It added that cognitive workers will be distinguished by their ability to frame the right questions, identify meaningful trade-offs and critically evaluate outputs, rather than merely process information.
The report called for a rethinking of India’s education system, warning that the traditional separation between formal education and work experience is increasingly untenable as AI begins to outperform entry-level workers on routine cognitive tasks. It proposed structured ‘earn-and-learn’ pathways that integrate high school, vocational and early university education with paid, credit-bearing industry experience.
At the school level, the survey urged greater emphasis on foundational skills such as literacy, numeracy, reasoning, communication and socio-emotional capabilities, which it stated will grow in importance as AI automates routine tasks. These skills, it argued, provide the base for adaptability across occupations, rather than narrow early specialisation.
Beyond white-collar services, the survey highlighted the need to map high-skill but understaffed jobs in non-office sectors, alongside investments in infrastructure and mobility to support worker transitions into emerging job clusters. Combined with public incentives, recognition of prior learning and short-form credentials, this would allow workers to move more seamlessly between education and employment.
The survey concluded that AI does not inevitably lead to job losses, but cautioned that poorly sequenced adoption could intensify labour displacement. Managing AI’s impact on employment, it argued, will depend on aligning technology deployment with institutional readiness, skills pipelines and labour-market adjustment capacity, so that productivity gains translate into broad-based economic benefits.
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