305 posts on compliance & regulation.
FedRAMP AI controls mapping becomes concrete when NIST SP 800-53 families are attached to the LLM request path. AC governs who may call a model, AU governs the decision record, SC protects the connection, SI handles monitoring, and CM governs route and policy changes.
A FedRAMP AI compliance review should test the authorization boundary, model inventory, identity propagation, least-privilege rules, data classification, event logging, evidence integrity, and continuous monitoring. This checklist translates those requirements into request-level tests an assessor can repeat.
This HITRUST AI compliance checklist covers scope, model inventory, identity propagation, protected-data classification, destination rules, response handling, audit integrity, vendor evidence, and recurring tests. Each item produces proof tied to actual AI traffic.
HITRUST AI audit evidence should connect each model request with the authenticated principal, protected data classification, approved destination, policy version, and enforcement result. That event-level chain gives healthcare and regulated teams testable proof beyond screenshots and application status logs.
Illinois hiring teams using AI analysis of applicant video interviews need evidence connecting notice, consent, approved sharing, deletion handling, and each model interaction. Request-level records can support technical reconstruction, while the application remains responsible for candidate notices and consent workflows.
HITRUST AI controls mapping should connect access control, information protection, logging, communications security, vendor management, and configuration practices to observable model requests. A narrow request-boundary map gives assessors clear mechanisms and evidence owners.
Illinois Artificial Intelligence Video Interview Act creates concrete governance work for enterprise AI: identify the processing, bind each request to identity and purpose, enforce data and model policy before transmission, preserve request-level evidence, and test deletion, incident, and exception paths. This guide turns the requirement into controls an assessor can inspect.
Illinois Artificial Intelligence Video Interview Act creates concrete governance work for enterprise AI: identify the processing, bind each request to identity and purpose, enforce data and model policy before transmission, preserve request-level evidence, and test deletion, incident, and exception paths. This guide turns the requirement into controls an assessor can inspect.
India Digital Personal Data Protection Act, 2023 creates concrete governance work for enterprise AI: identify the processing, bind each request to identity and purpose, enforce data and model policy before transmission, preserve request-level evidence, and test deletion, incident, and exception paths. This guide turns the requirement into controls an assessor can inspect.
India Digital Personal Data Protection Act, 2023 creates concrete governance work for enterprise AI: identify the processing, bind each request to identity and purpose, enforce data and model policy before transmission, preserve request-level evidence, and test deletion, incident, and exception paths. This guide turns the requirement into controls an assessor can inspect.
India Digital Personal Data Protection Act, 2023 creates concrete governance work for enterprise AI: identify the processing, bind each request to identity and purpose, enforce data and model policy before transmission, preserve request-level evidence, and test deletion, incident, and exception paths. This guide turns the requirement into controls an assessor can inspect.
ISO/IEC 23894:2023 creates concrete governance work for enterprise AI: identify the processing, bind each request to identity and purpose, enforce data and model policy before transmission, preserve request-level evidence, and test deletion, incident, and exception paths. This guide turns the requirement into controls an assessor can inspect.