AI’s costs fall unevenly across workers; IIT Madras paper flags surveillance, work stress
Whitepaper highlights risks to entry-level career paths and gaps in evidence on job quality and informal employment
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Updated - October 26, 2026 03:29 pm IST - CHENNAI
The whitepaper examines how AI automates tasks within jobs and how this can lead to changes in work, new roles or displacement.
Image for representation only | Photo Credit: Getty Images/iStockphoto
The costs of artificial intelligence (AI) adoption fall unevenly across workers, with entry-level jobs particularly at risk, according to a whitepaper by the Centre for Responsible AI (CeRAI) at the Indian Institute of Technology Madras (IIT-Madras).
“The entry-level career pipeline is especially at risk,” the paper says, highlighting differences in how AI affects entry-level and experienced workers, formal and informal workers, urban and rural workers, and employees in micro, small and medium enterprises (MSMEs) and large firms.
Titled ‘How AI Is Reconfiguring Work in India: A Task-Based Framework for Understanding Augmentation, Displacement, New Roles and the Changing Structure of Jobs’, the paper examines how AI automates tasks within jobs and how this can lead to changes in work, new roles or displacement.
The paper identifies differences in firms’ ability to adopt AI.
Large companies can absorb the fixed costs of integrating and customising advanced models, while MSMEs depend more on narrow, subsidised tools.
It also flags differences between English and regional-language work, noting that Indian-language AI performs less well on nuanced, code-switched conversations.
Automation is also creating new roles, including robot operators and AI escalation specialists.
However, the paper says its evidence does not systematically track whether such roles offer stable employment or piecework, a distinction that affects how much of the productivity gains reaches workers.
The paper says its framework is “largely silent” on changes in job quality because Indian evidence is limited.
It identifies wages, workplace monitoring, work intensity, stress and burnout, career progression, the quality of human interaction and responsibility for errors as areas requiring further study.
Among the questions it raises is whether AI will bring new forms of performance tracking, such as scoring the calls handled by BPO employees after AI has taken over routine queries, or using dashboards to track productivity among MSME shop-floor workers.
It also asks whether AI could leave workers handling a more demanding stream of exceptions after automating less-intensive tasks.
The authors caution that the available Indian sources do not systematically measure these dimensions.
Junior roles have traditionally served as apprenticeships, with routine tasks helping workers develop the judgement needed for senior positions, the paper says.
If AI automates tasks such as password resets, basic contract reviews and boilerplate coding, it raises questions about how new employees will acquire that experience.
The issue is particularly relevant to India’s IT, business process outsourcing (BPO), finance and professional-services sectors, which have historically hired large numbers of entry-level graduates.
One possible response is to redesign junior roles around supervising and correcting AI rather than performing routine tasks.
But the paper says it remains an open question whether firms will redesign career paths or simply hire fewer junior employees.
The paper notes that its framework relies largely on formal-sector evidence, despite informal work accounting for a substantially larger share of India’s workforce than the formal jobs examined in detail.
AI could affect informal workers indirectly through prices, consumer demand, credit access, platform management and business survival.
For instance, job losses in formal IT and BPO could reduce local spending that supports informal service providers.
AI-based credit scoring could also expand access to formal credit for some informal workers while excluding those without digital transaction records.
The paper does not quantify these effects and identifies informal employment as a priority for future research.
More broadly, it calls for India-specific research into AI’s labour-market effects and structured pathways to help workers transition as jobs change.
Artificial Intelligence / technology (general) / employment
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