Bharat Jobs Atlas India Job Market & AI Exposure Visualizer
Data: MoSPI PLFS 2025

India's workforce, one square each

Each rectangle's area is proportional to employment. Colour shows Digital AI Exposure — how much current, primarily-digital AI is reshaping each occupation.

Why this matters for India

60%

of formal-sector jobs in India are susceptible to automation by 2030, per NITI Aayog's Frontier Tech Hub.

1.5M–4M

projected tech-sector job swing by 2031 — a downside of 1.5M, or up to 4M new AI-era roles if India reskills.

3.1/10

is India's workforce-weighted AI exposure — low because ~35% of workers are in skilled agriculture and ~22% in elementary manual occupations.

Methodology & sources

Data foundation

Employment, rural/urban and gender splits are official statistics from the Ministry of Statistics & Programme Implementation (MoSPI) Periodic Labour Force Survey (PLFS) Annual Report 2025, Table 25 — the percentage distribution of workers (usual status, ps+ss) by NCO-2015 occupation group, sub-division and division, for Jan–Dec 2025.

Average monthly pay by occupation division is PLFS 2025 Table 51 (regular wage/salaried employees). Total workforce: 61.6 crore (616 million) persons aged 15+ employed in usual status (PIB/MoSPI, 2025).

Occupation names follow the ILO ISCO-08 structure; India's NCO-2015 mirrors ISCO-08 at the 2- and 3-digit level.

Rural share and female share per occupation are derived: PLFS Table 25 reports distributions within each population slice (e.g. what % of all female workers are in an occupation). We combine these with PLFS Statement 32 segment worker totals (male 415.8M, female 200.6M, rural 416.0M, urban 200.3M) to estimate the true within-occupation composition.

India has no official BLS-style occupational employment projection at the NCO-group level, so no "projected growth outlook" forecast is presented; sector context comes from NITI Aayog instead.

Digital AI Exposure score

This is a derived analyst estimate (0–10), adapted from the digital-work rubric published by Andrej Karpathy at karpathy.ai/jobs. It estimates how much current, primarily-digital AI will reshape each occupation — considering whether the work product is fundamentally digital (done on a computer: writing, coding, analysing, communicating) versus requiring physical presence.

Scores are assigned at the NCO sub-division (2-digit) level with a written rationale, and inherited by the 3-digit occupation groups within each sub-division. Anchors: 0–1 minimal (physical), 4–5 moderate, 6–7 high knowledge work, 8–10 very-high/maximum digital.

Caveat: These are rough estimates, not rigorous predictions. A high score does not mean a job will disappear — many high-exposure roles will be reshaped, not replaced, and demand may grow. Scores ignore demand elasticity, regulation and social preference for human workers.

Primary sources

  • MoSPI — PLFS Annual Report 2025 (Tables 25, 51 & Statement 32): mospi.gov.in
  • PIB — PLFS 2025 release (61.6 crore employed): pib.gov.in
  • DG E&T — National Classification of Occupations (NCO) 2015: dge.gov.in/nco-2015
  • ILO — International Standard Classification of Occupations (ISCO-08): ilo.org
  • NITI Aayog — Roadmap for Job Creation in the AI Economy (2025): niti.gov.in
  • Reference design — Andrej Karpathy, US Job Market Visualizer: karpathy.ai/jobs