Pakistan Job Market Visualizer

Visualizing 91 occupations from the Pakistan Bureau of Statistics Labour Force Survey 2024-25, covering 77.2M jobs across Pakistan's economy. Each rectangle's area is proportional to total employment. Color shows the selected metric. This is a research and exploration tool, not a formal economic publication. Inspired by Karpathy's US Job Market Visualizer.

▶ View the Digital AI Exposure scoring methodology

LLM-powered AI Exposure Scoring

Following the same methodology as Karpathy's original, each occupation was scored by an LLM (Claude) using a rubric calibrated for Pakistan's economy. The prompt evaluates how much current AI will reshape each occupation, considering Pakistan-specific factors like the large informal sector, lower digital infrastructure penetration, and the physical nature of most employment.

Rate the occupation's overall AI Exposure on a scale from 0 to 10.

AI Exposure measures: how much will AI reshape this occupation?
Consider both direct effects (AI automating tasks) and indirect
effects (AI making each worker so productive fewer are needed).

Pakistan-specific calibration:
- Pakistan's economy is ~81% informal with lower digital infra
- Physical/manual labor dominates (agriculture 33%, construction 10%)
- Digital adoption is growing fast in urban centers (fintech, freelancing)
- The IT/freelancing sector punches above its weight globally

Anchors:
0-1: Minimal. Entirely physical, hands-on, unpredictable environments.
     Examples: farm laborer, mason, rickshaw driver
2-3: Low. Mostly physical/interpersonal. AI helps peripherally.
     Examples: electrician, plumber, security guard, tailor
4-5: Moderate. Mix of physical and knowledge work.
     Examples: nurse, police officer, primary school teacher
6-7: High. Predominantly knowledge work.
     Examples: bank officer, accountant, journalist, lecturer
8-9: Very high. Almost entirely done on a computer.
     Examples: software developer, graphic designer, data analyst
10:  Maximum. Routine digital information processing.
     Examples: data entry operator, telemarketer, BPO agent
Caveat: These are rough LLM estimates, not rigorous predictions. A high score does not predict the job will disappear. Pakistan's large informal and physical economy means the aggregate AI exposure is lower than in the US. Software developers score 9/10 because AI is transforming their work, but Pakistan's IT exports could easily grow as each developer becomes more productive. The scores do not account for demand elasticity, regulatory barriers, or social preferences for human workers.
Data Sources: Pakistan Bureau of Statistics, Labour Force Survey 2024-25 (37th Round) · Employment Trend Report 2025 · Pakistan Standard Classification of Occupations (PSCO-2015, ISCO-2008 aligned) · Occupation-level employment derived from major group shares applied to 77.2M total employed (19th ICLS) · Wages from LFS Table 5.4 (average monthly wages by major occupational group) · AI Exposure scores generated via LLM following Karpathy methodology, calibrated for Pakistan.

Built by Talha Khan / Tech Arc Labs
If the AI exposure scores here have you thinking about your own business, the free AI Readiness Audit shows exactly where you stand and what to fix first. Five questions. No fluff.