Independent labor-market research · September 2026

Evaluating the Changing Demand for Human Labor

EOL Labor Analytics evaluates how AI, robotics, and automation move from technological capability to real labor-market effects across occupations, then translates that evidence into working outlooks for 2030 and 2035.

The first EOL assessment follows 20 occupations through a common analytical framework.

The objective is not a single automation score. It is a transparent view of technological progress, changing dependence on human labor, labor-market evidence, and the conditions that would alter the forecast.

20Occupations

6Transition stages

2030 / 2035Working outlooks

The EOL framework

Exposure is the beginning of the analysis, not the conclusion.

EOL follows the path from what technology can do today to whether technological change is actually appearing in hiring, staffing, wages, hours, and employment.

01 · Capability→

Can the technology perform relevant work?

Current capability in the occupational environment, not a hypothetical future system.

02 · Economic Viability→

Does substitution or augmentation make economic sense?

Cost, performance, workflow design, and the economics of deployment.

03 · Adoption→

Are capable systems actually being deployed?

Commercial adoption rather than demonstrations, pilots, or technical possibility alone.

04 · Task Subsumption→

How much of the task bundle is moving to technology?

Workflow-level substitution can matter even when no single system performs the entire occupation.

05 · Human Labor Dependency→

Does more output still require more human labor?

The central structural question is whether output can scale increasingly through machine capacity.

06 · Labor-Market Effects↓

Are upstream changes becoming visible in the labor market?

Hiring, hours, staffing ratios, wages, occupational entry, and employment provide the downstream test.

The stages are assessed separately. EOL does not mechanically combine them into an automation score.

Explore the methodology →

September 2026 assessment

The outlook varies sharply across occupations.

The chart shows EOL working ranges relative to the 2025 employment baseline. Switch between the 2030 and 2035 horizons. BLS structural projections appear as gold markers in the 2035 view.

Occupation

−20%0%+20%

EOL working range

O0115-1252

Software Developers Strong evidence tilt toward displacement

-2% to +3% -16% to +2% BLS +10.2%

O0213-2011

Accountants & Auditors Moderate evidence tilt toward displacement

-1% to +3% -7% to +3% BLS +5.0%

O0323-1011

Lawyers Moderate evidence tilt toward displacement

-1% to +3% -7% to +3% BLS +4.7%

O0443-4051

Customer Service Representatives Strong evidence tilt toward displacement

-5% to -2% -12% to -5% BLS −5.3%

O0541-3091

Sales Representatives of Services Strong evidence tilt toward displacement

-1% to +2% -8% to +2% BLS +2.7%

O0627-1024

Graphic Designers Strong evidence tilt toward displacement

-4% to 0% -12% to -3% BLS −1.7%

O0725-2031

Secondary School Teachers Balanced evidence

-1% to +2% -3% to +2% BLS −0.2%

O0817-2141

Mechanical Engineers Balanced evidence

+3% to +6% +4% to +9% BLS +11.2%

O0929-1215

Family Medicine Physicians Balanced evidence

+1% to +4% +2% to +6% BLS +3.3%

O1043-6014

Secretaries & Administrative Assistants Strong evidence tilt toward displacement

-5% to -2% -12% to -6% BLS −6.0%

O1137-2012

Maids & Housekeeping Cleaners Moderate evidence tilt toward displacement

-1% to +2% -10% to 0% BLS +0.6%

O1253-7062

Freight/Stock/Material Movers, Hand Strong evidence tilt toward displacement

-4% to 0% -13% to -3% BLS +1.8%

O1353-7063

Machine Feeders and Offbearers Strong evidence tilt toward displacement

-7% to -3% -16% to -11% BLS −13.1%

O1453-3032

Heavy & Tractor-Trailer Truck Drivers Strong evidence tilt toward displacement

-2% to +2% -14% to -3% BLS +3.8%

O1547-2061

Construction Laborers Balanced evidence

+3% to +6% +3% to +8% BLS +7.3%

O1635-3031

Waiters & Waitresses Moderate evidence tilt toward displacement

-2% to +1% -8% to 0% BLS +2.0%

O1735-3023

Fast Food and Counter Workers Strong evidence tilt toward displacement

-1% to +3% -12% to 0% BLS +5.8%

O1829-1141

Registered Nurses Balanced evidence

+3% to +6% +4% to +9% BLS +5.6%

O1931-1120

Home Health & Personal Care Aides Moderate evidence tilt toward displacement

+6% to +11% -5% to +10% BLS +18.1%

O2033-3051

Police & Sheriff’s Patrol Officers Moderate evidence tilt toward displacement

0% to +3% -3% to +3% BLS +3.5%

Forecast discipline

Why EOL develops its own forecasts alongside BLS

BLS remains the structural reference for every occupation EOL assesses.

Extending the sight picture when historical relationships are changing

BLS occupational forecasts are indispensable, but forecasts grounded in historical relationships are less reliable when those relationships are being disrupted. EOL Labor Analytics is built for that problem, using a new analytical framework to extend the sight picture of how AI and robotics may change the demand for human labor over the coming decade.

Read why EOL develops its own forecasts alongside BLS →

External probabilistic forecasts are also shown when a defensible occupation match exists. They are reference points, not ingredients mechanically averaged into the EOL range.

Structural reference

BLS

Official 2025–35 occupational projections and underlying demand structure.

Independent calibration

Metaculus

Probabilistic forecasts where EOL can establish a sufficiently strong occupational match.

EOL working outlook

EOL

Working ranges formed from the six-stage transition evidence, underlying demand, and observed labor-market effects.

Labor supply is a separate layer.

EOL also evaluates the worker pipeline feeding each occupation. Supply does not replace the demand forecast; it helps show whether future entrant flows are likely to reinforce, cushion, or conflict with the expected demand trajectory.

How EOL analyzes supply →

Companion publication

The End of Labor and the Last Worker

Long-form analysis of the broader economic, institutional, and social implications of the AI and robotics transition accompanies the occupation-level research published here.

Questions, corrections, or comments on the analysis? The best way to reach EOL Labor Analytics is through our Substack, The End of Labor and the Last Worker.

Read the publication ↗