AI and Employment
Displacement vs. Augmentation
The relationship between AI and employment is a central policy debate globally. Two competing frameworks dominate: displacement theory (AI replaces human labour, causing structural unemployment, particularly in routine cognitive and manual tasks) and augmentation theory (AI handles repetitive tasks, freeing humans for creative, relational, and complex work, generating new job categories). Empirical evidence is mixed — previous automation waves (industrial revolution, computerisation) ultimately created more jobs than they displaced, but the speed and breadth of AI capabilities raise concerns about whether labour markets can adapt fast enough.
- World Economic Forum "Future of Jobs Report 2025": projected 85 million jobs displaced and 97 million new jobs created by AI/automation by 2025, a net positive of 12 million roles
- India's IT sector: employs ~5.4 million (2025); NASSCOM projects AI-related skills will be required in 60–70% of these roles by 2027
- AI job creation categories: data annotation, model evaluation, AI ethics auditing, AI-human interface design, AI maintenance
- ILO (International Labour Organization): notes that women and low-skilled workers face disproportionate displacement risk from AI automation
● Tracked since February 14, 2026 · last seen February 24, 2026 · updates as the daily brief publishes