Glypticon's analysis draws on peer-reviewed research, government labor data, and live market signals. We combine multiple independent frameworks to generate career disruption timelines. The specific datasets that power our scoring:
01
O*NET Database
U.S. Department of Labor, Employment and Training Administration. O*NET OnLine.
onetonline.org
02
GPTs are GPTs
Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2023). "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models." arXiv:2303.10130.
03
AI Occupational Exposure
Felten, E., Raj, M., & Seamans, R. (2023). "Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses." Strategic Management Journal, 44(7), 1841–1861.
04
AI Exposure by Occupation
Penn Wharton Budget Model. (2025). "AI Exposure by Occupation." University of Pennsylvania.
budgetmodel.wharton.upenn.edu
05
Adaptive Capacity Index
Manning, A., & Aguirre, T. (2025). "How Adaptable Are American Workers to AI-Induced Job Displacement?" NBER Working Paper No. 34705.
We also incorporate live hiring data, layoff tracking, AI adoption signals, and demand substitution indicators from public sources.
Our methodology — how these inputs are weighted, combined, and translated into timeline estimates — is proprietary.