AI TRiSM (AI Trust, Risk and Security Management) is a governance framework, introduced by Gartner, for keeping AI systems explainable, reliable, private, and accountable once they run in production.
It groups four areas that teams usually handle separately: explainability and monitoring, ModelOps, AI application and data security, and privacy. The point of seeing them together is that a model can pass evaluation in a lab and still drift, leak, or become impossible to account for once real users and real data reach it.
The trust in AI TRiSM depends on the state of the data behind each run. If you cannot name the exact data a model used, you cannot explain the output, reproduce an incident, or prove compliance after the fact. A verifiable data state, with reproducibility and traceability built in, is what turns AI governance from a policy document into something a team can check.