AI-native compliance is a compliance workflow built to use artificial intelligence as part of the process, not just as a helper on the side. It can assist with collecting evidence, mapping controls to frameworks, drafting policies, summarizing audit findings, and routing items for review. In cybersecurity, this matters because compliance work is often slow, manual, and dependent on many disconnected systems.
In practice, AI-native compliance shows up in platforms that connect to cloud services, ticketing tools, endpoint data, and logs to keep control status current. Defenders use it to reduce repetitive work and improve coverage, but it only works well if the underlying data is trustworthy. Attackers or careless users can exploit weak governance by feeding bad inputs, hiding gaps, or accepting AI-generated output without verification. Strong audit trails, human review, and clear scope are still required.