Enterprises today face a growing AI risk surface. From unauthorized GenAI use to algorithmic bias and data leakage, the speed of AI innovation often outpaces governance. Yet, those who get AI trust and security right can transform risk into a competitive advantage.
The AI TRiSM framework, introduced by Gartner and expanded upon in the joint white paper by BigID and Databricks, redefines how organizations manage risk in the age of AI. By embedding trust, risk, and security management into the data and AI lifecycle, enterprises can ensure compliance, protect brand reputation, and unlock greater value from AI investments.
BigID extends AI TRiSM through its AI Security Posture Management (AI SPM) and AI Risk Assessment capabilities. These tools automatically detect unauthorized AI use, quantify model-specific risks, and validate that training data is compliant and appropriate for use. Combined with Databricks Unity Catalog, organizations gain policy-based governance, data masking, and lineage tracking across all AI data assets.
Accenture’s role brings this all together, enabling global organizations to implement AI TRiSM in complex enterprise environments, integrate governance into existing MLOps pipelines, and accelerate adoption through proven data strategies.
Together, BigID, Databricks, and Accenture help enterprises:
- Identify and mitigate AI-specific risks across models and data sources
- Improve data quality and reduce exposure by automating remediation
- Ensure AI systems meet regulatory and ethical standards
- Build resilience and trust into AI operations
Organizations that take a proactive approach to AI risk don’t just comply—they differentiate. AI TRiSM transforms AI governance from a compliance checkbox into a driver of innovation, customer confidence, and operational efficiency.
Learn how to make AI risk your next advantage.
Download the white paper to explore how BigID and Databricks operationalize AI TRiSM.
Join the November 12 webinar The Power of Clean Data: AI TRiSM for Trusted and Responsible AI.
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