Glossary
Updated
AI TRiSM moves beyond simple regulatory compliance to address the technical realities of AI in production. According to Gartner, it rests on four pillars: Explainability (understanding model logic), ModelOps (lifecycle management), AI Application Security (defense against attacks), and Data Privacy. For enterprise governance teams, adopting AI TRiSM means shifting from "checking boxes" to implementing active defenses against threats like model poisoning and adversarial attacks.
Example
A fintech company adopts AI TRiSM for its credit scoring model. Instead of just documenting the model for regulators (Governance), they implement "Adversarial Training" to ensure hackers cannot fool the score (Security) and "Drift Detection" to ensure the model remains accurate over time (Reliability), creating a continuous loop of trust.