What is AI Risk Management
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Definition
As organizations scale the use of AI across critical processes, they face a new category of risks that traditional governance frameworks do not fully address. These risks may relate to model performance, bias, explainability, data quality, regulatory compliance, security, or unintended impact.
AI Risk Management provides a structured approach to identifying, assessing, mitigating, and monitoring these risks throughout the entire AI lifecycle. It ensures that AI systems remain trustworthy, compliant, and aligned with business objectives.
Within the Yields AI Governance Solution, AI Risk Management is fully embedded into governance workflows, enabling organizations to manage AI risks in a consistent, traceable, and auditable way.
About the
Author(s)
Behind Yields is a team of experts in risk, regulation, and technology. When we write as Yields, we share our combined knowledge to make complex topics clear and actionable.
