Working outlooks
2030 and 2035 ranges built from the six-stage transition assessment, underlying demand, labor-market evidence, and explicit conditions that would change the view.
An independent, non-commercial research project examining how AI, robotics, and automation may change the demand for human labor.
EOL uses BLS as the structural reference, independent probabilistic forecasts as calibration where appropriate, and an occupation-specific framework to test whether emerging technology is weakening historical relationships between output, tasks, staffing, and employment.
2030 and 2035 ranges built from the six-stage transition assessment, underlying demand, labor-market evidence, and explicit conditions that would change the view.
Occupation-specific analysis of education, licensure, training, turnover, and worker entry shows where future supply may reinforce or complicate changing demand.
Prior EOL assessments and external forecast snapshots are preserved so revisions can be evaluated against subsequent evidence and realized outcomes.
EOL draws on government statistics, academic research, forecasting platforms, industry evidence, and company deployment information. Use of those sources does not imply affiliation or endorsement, and company or vendor evidence is used for the claims it can support rather than treated as a neutral labor-market forecast.
The companion Substack explores the broader economic, institutional, and social implications of the AI and robotics transition. EOL Labor Analytics provides the occupation-level analytical infrastructure beneath that larger discussion.
Questions, corrections, methodological concerns, and other feedback are welcome. The best way to contact EOL Labor Analytics is through The End of Labor and the Last Worker on Substack.