California Generative AI: Training Data Transparency: Compliance Checklist

Compliance checklist

Run through these items to scope your obligations under California Generative AI: Training Data Transparency. Not legal advice; verify with counsel before acting.

1. Confirm scope: does the law apply to your operations? See Who Must Comply or use the Compliance Checker.
2. Inventory in-scope AI systems and classify them by role (developer/deployer) and decision type.
3. Address each obligation:
   • transparency — Publicly post on the developer's website a high-level summary of training datasets used for any generative AI system or service made available to Californians on or after January 1, 2022.Cal. Civ. Code § 3111
   • documentation — Address each statutory element in the dataset summary — sources or owners, how the data furthers the system's purpose, number and types of data points, copyright/trademark/patent or public-domain status, purchased-or-licensed status, presence of personal information or aggregate consumer information, any cleaning or modification, first-use dates, collection time period, and any use of synthetic data generation.Cal. Civ. Code § 3111
   • transparency — Refresh and re-post the public training-data summary before each subsequent public release or substantial modification of a covered generative AI system, so the disclosure stays current rather than ending at the initial January 1, 2026 deadline.Cal. Civ. Code § 3110
4. Adopt a federal control framework: NIST AI RMF or ISO/IEC 42001 to demonstrate due care.
5. Document evidence of compliance for each obligation, refreshed at the cadence the law requires.
6. Build the AG-notification path if the law requires it (Colorado, California SB 53).
7. Set the refresh cadence — annual for most impact-assessment regimes; continuous for monitoring.