California Finalizes ADMT Rules Under CCPA, Effective 2026

November 07, 2025
California has introduced new rules under the California Consumer Privacy Act focusing on cybersecurity audits, risk assessments, and automated decision-making technology. The regulations take effect in 2026, with compliance for businesses using ADMT required by 2027.

California has introduced new rules under the California Consumer Privacy Act (CCPA) that will significantly affect how businesses use automated decision-making technology (ADMT), according to a Bloomberg Law report. The regulations, which also cover cybersecurity audits and risk assessments, will take effect on January 1, 2026, with compliance for companies using ADMT in significant decision-making required by January 1, 2027.

The California Privacy Protection Agency (CPPA) began drafting the new regulations in November 2024. The rulemaking process drew responses from technology companies, advocacy groups, and public officials, many of whom expressed concern that the proposed definition of ADMT was too broad. Governor Gavin Newsom urged the agency to ensure the rules did not unintentionally limit innovation in the technology sector.

The new framework will require organizations operating in California to reassess how they secure personal data, conduct risk assessments, and manage automated systems that influence decisions about consumers. Meeting the applicability thresholds set by the CPPA could mean substantial operational changes for companies managing large volumes of personal data or relying heavily on automation.

We hope you enjoyed this article.

Consider subscribing to one of our newsletters like AI Policy Brief or Daily AI Brief.

Also, consider following us on social media:

Subscribe to AI Policy Brief

Weekly report on AI regulations, safety standards, government policies, and compliance requirements worldwide.

Market report

AI’s Time-to-Market Quagmire: Why Enterprises Struggle to Scale AI Innovation

ModelOp

The 2025 AI Governance Benchmark Report by ModelOp provides insights from 100 senior AI and data leaders across various industries, highlighting the challenges enterprises face in scaling AI initiatives. The report emphasizes the importance of AI governance and automation in overcoming fragmented systems and inconsistent practices, showcasing how early adoption correlates with faster deployment and stronger ROI.

Read more