Executive frameworks for managing the technical risk associated with Generative AI and automated systems. We align organizational AI deployment with the NIST AI RMF 1.0 to ensure safety, algorithmic accountability, and regulatory compliance in the age of agentic AI.
An AI risk assessment identifies, analyzes, and treats risks specific to AI systems: bias, hallucination, data provenance, and decision accountability. The NIST AI RMF 1.0 structures the process into four functions: Govern, Map, Measure, and...
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In 2000, Latanya Sweeney at Carnegie Mellon demonstrated that 87% of the U.S. population becomes uniquely identifiable from three data points: five-digit ZIP code, gender, and date of birth [Sweeney 2000]. She proved it by...
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AI governance is the system of policies, oversight mechanisms, and accountability structures directing how organizations develop, deploy, and monitor artificial intelligence. Three frameworks define the 2026 standard: the EU AI Act (enforcement August 2, 2026),...
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