Demand
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.
About the project
About EOL Labor Analytics
An independent, non-commercial research project examining how AI, robotics, and automation may change the demand for human labor.
Purpose
Occupation-level analysis for a changing relationship between technology and labor
EOL follows 20 deliberately selected occupations across knowledge and physical work to study different ways technology may alter demand for human labor. This focused approach favors depth, comparative insight, and sustained monitoring over a comprehensive occupation census. EOL uses BLS as a structural reference and independent probabilistic forecasts as calibration where appropriate, testing whether emerging technology is weakening historical relationships between output, tasks, staffing, and employment.
Supply
Entrant pipelines
Occupation-specific analysis of education, licensure, training, turnover, and worker entry shows where future supply may reinforce or complicate changing demand.
Accountability
Forecast history
Prior EOL assessments and external forecast snapshots are preserved so revisions can be evaluated against subsequent evidence and realized outcomes.
Research independence
Source facts and EOL judgments remain separate
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.
Founder & Principal Researcher
Who is behind EOL
EOL is an independent research effort. Identifying the researcher responsible for its analyst-directed judgments is part of that transparency.
Al Baharmast, Ph.D.
Founder & Principal Researcher
Al Baharmast is the Founder & Principal Researcher of EOL | Labor Analytics. He brings decades of experience at the intersection of technology, business, and organizational change. He founded and led a digital transformation consultancy for more than two decades, advising organizations on complex technology-enabled transformations, and spent nearly two decades as a university business professor.
His work on EOL draws on that combination of technology, business, and academic experience to examine a question that increasingly cuts across all three: how advances in AI, robotics, and automation are changing the demand for human labor.
Companion Publication
The End of Labor and the Last Worker
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.
Contact
Questions, corrections, methodological concerns, and other feedback are welcome. The best way to contact EOL | Labor Analytics is by email at research@endoflabor.org, through The End of Labor and the Last Worker on Substack.