India needs its own methodology to track how jobs and tasks are changing, she said, particularly as disruption may show up through slower hiring and changing roles long before it appears as mass unemployment.
Ghosh said the Indian government and industry have put far more energy into “AI infrastructure, compute, and skilling announcements”.
“Much less into measuring what is happening to jobs and planning the transition for the people affected,” he said.
But better measurement does not mean every use of AI should be allowed to move at the same pace, experts cautioned.
“India should not slow general-purpose adoption, but it should slow deployment where error, opacity or concentration can permanently harm people,” AI&Beyond co-founder Bindra said, citing areas such as hiring, credit, welfare, healthcare and workplace surveillance.
Venkatesan from the Institute for Human Flourishing said a key goal should be to ensure AI helps small businesses and self-employed workers earn more, rather than simply becoming more efficient.
For example, AI tools could help small businesses find more customers, qualify for loans and navigate regulatory requirements, he said.
Venkatesan suggested using existing networks such as self-help groups, farmer organisations, business associations, local accountants and government agricultural advisers to help small businesses and informal workers adopt AI, rather than relying on direct-to-user apps.
The government could also use AI to support decision-making by frontline health workers and teachers, rather than for surveillance or to replace staff, Venkatesan said.
“India cannot shape the technological frontier, but it can and must shape the adoption pathway,” he said.
