India’s IT Secretary S Krishnan has provided a reassuring perspective on the impact of Artificial Intelligence (AI) on the domestic labour market. He asserted in an interaction with news agency PTI that
India faces a significantly lower risk of AI-driven disruption to cognitive and white-collar jobs compared to Western economies. Krishnan attributed this resilience to the unique structural composition of the Indian workforce and the nature of its professional landscape.
The ‘White-Collar’ Proportion Argument
Krishnan pointed out that the proportion of white-collar roles within India’s overall workforce is considerably smaller than in the West. While Western economies are heavily dominated by knowledge workers whose roles involve the very “cognitive tasks”—reasoning, problem-solving, and data synthesis—that AI excels at, India’s broader economy remains diverse across manufacturing, agriculture, and services. Consequently, even as AI targets mental rather than manual labour, the “total exposure” of the Indian economy to this specific disruption is naturally buffered by its demographic and occupational variety.
STEM Dominance as a Competitive Edge
A crucial factor in Krishnan’s optimistic outlook is India’s dominance in STEM (Science, Technology, Engineering, and Mathematics) fields. He argued that most white-collar jobs in India are technical in nature, which paradoxically places these workers in a better position to harness AI rather than be replaced by it. Instead of merely consuming AI outputs, the Indian workforce is increasingly involved in building and deploying sector-specific AI applications. This shift from generic models to “purpose-built” tools for industries like healthcare and agriculture is expected to generate a “Y2K-like” moment for the Indian IT sector, creating a surge in demand for trained professionals.
Humans-in-the-Loop and ‘Hallucinations’
The IT Secretary also addressed the current limitations of generative AI, specifically the issue of AI hallucinations—where models confidently present incorrect information as fact. Krishnan noted that as long as these systems remain prone to error, the need for “humans-in-the-loop” to oversee, verify, and curate AI outputs will persist for a much longer duration. This requirement for human oversight ensures that cognitive jobs will evolve into supervisory roles rather than disappearing entirely.
The Path Ahead: Upskilling Over Automation
While acknowledging that AI is the first technology to directly challenge knowledge workers, the government’s focus remains firmly on upskilling and reskilling. Krishnan emphasised that the real economic impact will come from the wide-scale deployment of AI in productive sectors, which will necessitate a massive workforce capable of managing these new systems. By focusing on “frugal innovation” and India-specific foundation models, the country aims to turn a potential disruption into a tool for social good and economic prosperity.
