Post-Labor Economy Displacement Scenario Model

283 occupations · 138.8M workers · 90% of U.S. employment · BLS OEWS May 2024

How it works: Everybody has an opinion, including you. The model is set to allow you to input your own assumptions for each employment group. Think we've overestimated the unemployment rate for certain job categories? Adjust the sliders as much as you like to match your estimates. Each U.S. occupation has been scored 1 to 5 for Post-Labor Vulnerability based on AI displacement risk and consumer spending dependency. Adjust the displacement percentages below to model what happens to unemployment. You can see all of the 283 occupations covering 90% of all jobs on the All 283 Occupations tab.

Your Assumptions

Historical Comparison

Most Affected Occupation Categories

5 Critical Vulnerability

  • Cashiers 3.3M workers
  • Retail Salespersons 3.6M workers
  • Fast Food & Counter Workers 3.6M workers
  • Customer Service Reps 2.8M workers
  • Data Entry Keyers 0.2M workers

4 High Vulnerability

  • Market Research Analysts 0.9M workers
  • Bookkeeping & Accounting Clerks 1.5M workers
  • Assemblers & Fabricators 1.6M workers
  • Heavy & Tractor-Trailer Truck Drivers 2.0M workers
  • Retail Supervisors 1.2M workers
Methodology: Employment data from BLS Occupational Employment & Wage Statistics (OEWS), May 2024. 283 detailed occupations covering 138.8M workers (90% of total U.S. employment). Remaining 10% of employment assigned to Score 3 (Moderate). This is a scenario analysis tool, not a forecast. Employment-weighted scoring framework developed for Post Labor Investing.

AI Displacement Risk (1 to 5)

How susceptible is this occupation to replacement by AI, robotics, or automation?

ScoreLabelDescription
1Very LowPhysical work in unpredictable environments, deep human interaction required. Robotics decades away at current wage points.
2LowMostly physical or requires significant human judgment in variable settings. AI augments but doesn't replace.
3ModerateMix of automatable and non-automatable tasks. Occupation shrinks but doesn't disappear.
4HighPrimarily routine cognitive or data-processing work. AI can handle most core tasks.
5Very HighHighly structured, repetitive tasks. Already being actively automated by current technology.

Consumer Dependency (1 to 5)

How much does this occupation depend on continued consumer spending by employed people?

ScoreLabelDescription
1MinimalEssential services, government-funded, or demographically driven demand. Insulated from consumer spending cycles.
2LowPrimarily B2B, infrastructure, or capital-goods oriented. Indirect consumer exposure only.
3ModerateMixed exposure. Some consumer-facing, some institutional demand.
4HighPrimarily consumer-facing. Revenue directly tied to household spending.
5Very HighAlmost entirely dependent on discretionary consumer spending. Demand collapses if consumers stop spending.

Post-Labor Vulnerability (1 to 5)

The combined assessment: how exposed is this occupation to the post-labor economy transition?

ScoreLabelDescription
1ResilientGovernment-funded, demographically driven, or AI-complementary. Occupation likely grows or holds steady.
2Low VulnerabilityModest impact expected. Physical work, essential infrastructure, or roles that benefit from AI augmentation.
3ModerateMeaningful but manageable disruption. Occupation shrinks but doesn't disappear. Workers must adapt.
4HighSignificant job losses likely. Occupation exists but at much smaller scale.
5CriticalOccupation could largely disappear or shrink more than 50%. Both highly automatable AND dependent on consumer spending.

Combined Score

Simple average of AI Displacement Risk, Consumer Dependency, and Post-Labor Vulnerability. Employment-weighted averages weight by headcount to show aggregate labor market exposure.

About the Data

This table presents 283 U.S. occupations scored across three dimensions: AI Displacement Risk, Consumer Dependency, and Post-Labor Vulnerability. Together, these scores produce a Combined Score that estimates each occupation's overall exposure to the post-labor economy transition.

Employment and wage data are sourced from the Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) survey, May 2024. The 283 occupations listed cover approximately 138.8 million workers, representing 90% of total U.S. employment.

How the scores were generated: The vulnerability scores were produced by AI (Claude, developed by Anthropic) using a structured scoring framework. Each occupation was evaluated against defined criteria for each dimension, with scores ranging from 1 (minimal risk/dependency) to 5 (critical risk/dependency). The Combined Score is a simple average of the three dimensions.

While AI scoring provides consistency and scale across hundreds of occupations, these scores reflect probabilistic assessments, not certainties. Individual occupations may be affected differently depending on the pace of technological adoption, regional factors, and policy responses. This is an analytical framework for thinking about the post-labor transition, not a definitive prediction.

You can review the full scoring criteria on the Scoring Methodology tab.

AI = AI/Automation Risk CD = Consumer Dependency PLV = Post-Labor Vulnerability Scores: ● 1 ● 2 ● 3 ● 4 ● 5
Occupation ▿ Group ▿ Employment ▿ Mean Wage ▿ AI CD PLV Combined