NIST’s Blueprint for AI Security: How Data Trust Enables AI Success

The article argues that AI reshapes cybersecurity and should be managed by extending NIST CSF 2.0 and the AI Risk Management Framework with a focus on “data trust”—demonstrable, safe, and appropriate data use across AI workflows. It links CSF functions (Govern, Identify, Protect, Detect, Respond/Recover) with AI RMF (Govern, Map, Measure, Manage) and recommends practices including continuous data visibility, context-driven risk evaluation, data-centric enforcement, responsible defensive use of AI, and continuous verification. The outcome is NIST-aligned, integrated risk management that enables safer AI adoption, reduces data exposure and false positives, and boosts confidence in AI-driven operations.