AI Governance & AIMS
ISO/IEC 42001 Advisory
Operational AI Governance & AIMS Readiness
AIMS Scope & AI System Inventory
Define the organizational context, interested parties, Artificial Intelligence Management System (AIMS) scope, and a decision-useful inventory of AI systems, models, providers, owners, data dependencies, and business use cases.
ISO/IEC 42001 Readiness & Gap Assessment
Assess current governance, processes, controls, documentation, and evidence against ISO/IEC 42001 requirements. Identify material gaps, accountable owners, dependencies, priorities, and a practical implementation roadmap.
AI Risk & Impact Assessment
Establish repeatable methods to identify, analyze, evaluate, treat, and monitor AI risks and organizational impacts across the AI lifecycle, including security, privacy, reliability, transparency, and human consequences.
Policies, Controls & Human Oversight
Translate responsible AI principles into policies, objectives, roles, decision rights, human oversight, control applicability, operational procedures, and measurable accountability that teams can execute.
Third-Party AI Risk & Operational Assurance
Strengthen governance for externally provided models, platforms, agents, data, and services through supplier due diligence, contractual expectations, monitoring, incident handling, change control, and evidence-based assurance.
AIMS Implementation & Certification Readiness
Build a phased AIMS implementation plan covering documentation, awareness, metrics, performance evaluation, internal review, corrective action, continual improvement, and preparation for independent certification assessment.
Why This Matters
Govern AI with clarity, accountability, and evidence.
AI governance must work across leadership, risk, legal, privacy, cybersecurity, engineering, data, procurement, and operations. As a Certified ISO/IEC 42001 Lead Implementer, I combine formal Artificial Intelligence Management System (AIMS) capability with 18+ years in cybersecurity operations, detection engineering, security-product development, audit, GRC, and AI-assisted defense to help organizations turn governance requirements into operational controls and defensible evidence.
- Operational Perspective: Connect AI governance with the systems, data, security controls, workflows, and teams that operate AI in practice.
- Executive Accountability: Establish ownership, decision rights, escalation paths, risk acceptance, and meaningful oversight.
- Integrated Risk: Connect responsible AI with cybersecurity, privacy, enterprise risk, third-party risk, and operational resilience.
- Audit-Ready Evidence: Define measurable objectives, records, metrics, reviews, corrective actions, and evidence that demonstrate governance is operating.
- Practical Roadmap: Prioritize implementation around business context, risk, readiness, resources, and certification objectives.