AI TRiSM stands for Artificial Intelligence Trust, Risk, and Security Management. It is a framework that encompasses the tools, processes, and governance models used to ensure that AI models are explainable, ethical, secure, and compliant. AI TRiSM addresses emerging risks related to the use of artificial intelligence and machine learning by providing strategies to manage bias, drift, adversarial attacks, and regulatory compliance.
Origin and Importance:
The term was popularized by Gartner, who identified AI TRiSM as a critical discipline for organizations deploying AI at scale. As AI adoption accelerates across industries, managing its trustworthiness and associated risks has become a top priority to build confidence among stakeholders and comply with evolving global regulations like the EU AI Act, HIPAA, and GDPR.
Model Explainability
Privacy and Data Protection
AI Governance and Lifecycle Oversight
Adversarial Robustness
Bias and Fairness Auditing
Compliance Monitoring
Without proper oversight, AI systems can pose reputational, operational, legal, and ethical risks. AI TRiSM helps organizations maintain control over rapidly evolving technologies and ensure AI deployments are secure, compliant, and trusted.
Gain better visibility into AI model security, including protection against adversarial attacks, model theft, and unauthorized use.
Ensure AI systems are aligned with privacy regulations, data usage policies, and auditability standards.
Improve transparency by designing interpretable models and applying fairness, accountability, and explainability principles.
Increase trust with customers and regulators by demonstrating responsible AI practices, leading to safer AI-driven decision-making.
