The debate over AI and jobs in India is shifting. A recent white paper from IIT Madras suggests the real story is not about mass job replacement, but a fundamental change in what jobs actually involve from day to day.
The Core Argument: Tasks, Not Jobs
Researchers at IIT Madras's Centre
for Responsible AI (CeRAI) argue that we should analyse AI's impact by looking at individual tasks within a job, not the entire occupation. Most jobs are a collection of different duties, and AI is currently capable of automating only some of them, particularly those that are repetitive and process-oriented. For example, a customer service agent may find that an AI bot now handles basic password resets, freeing them up to manage complex and sensitive customer complaints that require human judgment. Similarly, a junior accountant might spend less time on manual data entry and more on analysing the output generated by AI. This shifts the conversation from 'job loss' to 'job reconfiguration'. The IIT Madras paper, titled 'How AI Is Reconfiguring Work in India', posits that this change is already underway across sectors like IT, BPO, finance, and professional services.
The Challenge for Entry-Level Roles
A significant concern raised by the IIT Madras paper is the impact on career progression, especially for new entrants to the workforce. Historically, junior roles have served as an apprenticeship, where employees learn the fundamentals of an industry by performing routine, individually low-value tasks that collectively build professional judgment. If AI automates these foundational tasks—like basic coding for a software engineer or invoice processing for an accountant—it raises a critical question: how will the next generation of workers acquire the experience needed to advance to senior positions?. Companies may need to fundamentally rethink their training and development programs. Instead of learning by doing repetitive tasks, entry-level roles might evolve to focus on supervising AI systems, validating their outputs, and handling escalations, which requires a different initial skill set.
From Augmentation to Redesign
The impact of AI will not be uniform; it will depend on factors like cost, regulation, and how businesses choose to integrate the technology. The IIT Madras paper identifies two main patterns. One is 'augmentation', where humans remain in charge and use AI as a productivity tool, like a lawyer using AI for rapid document review while still owning the legal strategy. The other is 'redesign', where AI performs most of the task and a human's role shifts to verification and oversight. In India's cost-sensitive service economy, affordable, task-specific AI for things like BPO calls or quality checks is spreading quickly. A recent survey of IT firms confirmed this, finding that AI adoption has primarily led to productivity gains, with employment effects concentrated at the entry-level hiring stage rather than through widespread layoffs.
The New Skill Imperative
This transformation makes upskilling and reskilling more critical than ever. The focus is shifting from performing routine processes to possessing uniquely human skills. Reports from industry bodies like NASSCOM reinforce this, highlighting a gap between the number of workers who use AI and those who are truly 'AI-native'—able to orchestrate, exercise independent judgment, and use AI to innovate. While 65% of employees lack confidence or have no exposure to AI tools, employers are increasingly prioritising demonstrable AI skills over traditional degrees. The skills in demand are not just technical, like Python or machine learning, but also foundational capabilities like critical thinking, problem_solving, and adaptability. Government and industry are responding with initiatives like the AI Skills Passport to help bridge this gap, but the onus is on both individuals and organisations to embrace continuous learning.
