S&P 500 AI and Governance-Risk Disclosure Panel, 2020–2024

This dataset provides a firm-year panel of non-financial S&P 500 companies for the period 2020–2024. It was prepared to support empirical analysis of the relationship between artificial intelligence disclosure salience and governance-risk disclosure in large U.S. public firms. The final panel contains 2,106 firm-year observations and 424 unique firms, after excluding financial-sector firms, observations without usable disclosure information, observations with missing core controls, and duplicate CIK-year records.
The main panel includes firm identifiers, including zero-padded CIK codes, company names, ticker symbols, year, and sector classification, together with disclosure-based variables and financial controls. The key text-based variables are AI disclosure salience, governance-risk disclosure counts, and the log-transformed governance-risk measure. Additional variables include profitability, leverage, sales growth, firm size, Big 4 auditor status, CEO duality, and related firm-year controls.
The workbook also includes supporting documentation sheets: a README, a variable guide, sample checks, and dictionary terms used to identify AI-related and governance-risk language.
The dataset is intended for academic research, methodological illustration, and replication of the empirical workflow described in the related manuscript. Users should consult the accompanying variable guide and dictionary sheets before reusing or extending the data.