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.
Your compliance team runs a quarterly access review. The SSO dashboard shows 14 approved SaaS applications. Then your network monitoring team flags 47 outbound API connections to AI service endpoints nobody approved. Thirty-three AI tools running...
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How many AI tools process protected health information (PHI) in your organization right now? Not the ones your compliance team approved. All of them. The AI scribe your physicians adopted six months before anyone signed...
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Non-human identities outnumber human users 82-to-1 in enterprise environments [CyberArk 2025]. Service accounts, API keys, bot credentials, and AI agent tokens now constitute the largest attack surface in the average organization. Most identity and access...
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Every AI risk assessment I have reviewed in the last two years shares the same structural flaw. The organization catalogs the AI systems. Lists the vendors. Documents the use cases. Then applies the same risk...
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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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Three regulatory frameworks converge in 2026 to create the first global standard for governing artificial intelligence. The EU AI Act enters general application August 2, 2026, when GPAI model obligations and most operational provisions become...
Read the GuideOne compliance analysis per week from Josef Kamara, CPA, CISSP, CISA. Federal and private compliance, written for practitioners.