THE SHORT ANSWER
AI is changing work through task automation, human augmentation, workflow redesign and new expectations about speed and quality. Its effect depends on the task, technology, organization and choices about adoption; exposure to AI is not the same as a job being eliminated.
Four changes can happen at the same time
| Change | What it means |
|---|---|
| Automate | A system performs a bounded task with limited human handling |
| Augment | A person uses AI to research, draft, compare or execute faster |
| Transform | The workflow, handoffs and quality checks are redesigned |
| Create | New tasks appear in evaluation, governance, integration and service design |
Exposure is a possibility, not an employment forecast
The ILO–NASK 2025 index assesses the overlap between generative-AI capabilities and nearly 30,000 occupational tasks. It concludes that transformation is generally more plausible than full automation because occupations combine tasks and many still require human involvement.
The study estimates potential exposure under stated assumptions. Adoption costs, regulation, work organization, demand and new tasks all affect what happens in practice.
Evidence & context: International Labour Organization and NASK
The same technology produces uneven results
A customer-support field study of 5,179 agents found average productivity gains after AI assistance, with larger gains among less-experienced workers. That result is evidence for one tool in one setting—not a universal productivity rate.
South Asian job-posting evidence also separates exposure from complementarity. India-relevant planning therefore needs local role, sector and access information rather than imported headlines.
Evidence & context: National Bureau of Economic Research · World Bank
Respond with a work map, not a prediction
- Name the outcome your role is responsible for.
- List the tasks and handoffs that produce it.
- Test where AI can assist or automate within a clear quality threshold.
- Keep accountable judgment and sensitive interactions assigned.
- Measure quality, time, risk and rework before expanding.
Sources & further reading
- Generative AI and Jobs: A Refined Global Index of Occupational Exposure
International Labour Organization and NASK. A 2025 working paper combining task-level data for nearly 30,000 occupational tasks, expert validation, model-assisted scoring and harmonized employment data. Exposure indicates potential task transformation; it is not a forecast that a job will disappear.
- Skills in the AI Age
OECD. A 2026 synthesis of cross-country evidence on AI adoption, task change and complementary skills. Country, sector and firm differences mean its findings do not produce one universal skills ranking.
- South Asia Development Update: Jobs, AI, and Trade
World Bank. A 2025 regional report using labour data and job postings to distinguish AI exposure from human complementarity in South Asia. Online listings underrepresent informal and some local labour markets, so the findings are directional rather than a complete picture of India or the region.
- Generative AI at Work
National Bureau of Economic Research. A field study of 5,179 customer-support agents during a staggered AI-assistant rollout, later published in the Quarterly Journal of Economics. Results varied by experience and task and should not be generalized to all occupations.
Examples and exercises are illustrative unless attributed to a source. No independent expert review is claimed.
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