The Upskilling Gap: How Time Poverty and Unpaid Labor Limit Women in the AI Era

Syllabus: Indian Economy and issues relating to planning, mobilization of resources, growth, development and employment.

Context

  • Rapid expansion of AI-driven workplaces has intensified job insecurity and upskilling pressures.
  • Working women already face near 80-hour work weeks due to unpaid domestic and care work.
  • AI threatens paid jobs, but unpaid labour remains invisible and uncompensated.

Time Use and Gendered Work Burden

  • Time Use Survey 2024 shows around 40% women participate in the labour force.
  • Women experience stacking of paid and unpaid work, not substitution.
  • Average working woman spends 9.6 hours daily on combined paid and unpaid work.
  • Unpaid work includes childcare, eldercare, cooking, cleaning, and subsistence activities.
  • Burden peaks during 25–39 years, crossing 70 hours weekly.

Male–Female Work Hour Disparity

  • Men average 8.6 hours daily on combined work.
  • Over 80% of men’s work time is paid, with minimal unpaid responsibilities.
  • Men’s total weekly work ranges between 54–60 hours across life stages.
  • Gender gap widest during prime working years due to unequal caregiving roles.

Impact on Health and Self-Development

  • Women compensate by reducing sleep and self-care.
  • Women sleep 2–2.5 hours less weekly during prime working years.
  • Women spend 10 hours less per week on self-development than men.
  • Gap widens to 11–12 hours weekly during ages 25–39.
  • Reduced learning time weakens AI-era skill transitions.

Economic Implications

  • Women contribute only 17% of India’s GDP, despite high labour input.
  • Unpaid work is excluded from national income calculations.
  • Nearly 40% women outside labour force cite household duties (PLFS).
  • AI risks worsening exclusion as women’s jobs are more automation-prone.
  • Algorithmic performance metrics ignore caregiving constraints.

Policy Imperatives

  • Empowerment requires replacement of drudgery, not job addition alone.
  • Policies must adopt outcome-based approaches using time-use data.
  • Gender budgets should prioritise time-saving infrastructure:
    • Affordable childcare and eldercare
    • Piped water and clean energy
    • Safe and accessible public transport
  • Expand flexible, lifelong upskilling aligned with women’s time constraints.
  • Scale initiatives like India AI Mission and AI Careers for Women.

Conclusion

  • Women’s time poverty constrains productivity, growth, and AI readiness.
  • Valuing and freeing women’s time is essential for Viksit Bharat 2047.

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