Course · NCAIRG

NSD Certified AI Risk and Governance Program

Govern AI, from the model to the autonomous agent.

A course by the Cybersecurity & AI Initiative, an ISAC Foundation centre.

Length
18 hours
When
Weekends: Saturday and Sunday, two hours each
Format
Live instructor-led professional cohort
Certification
NSD certification: a knowledge assessment and a case-based enterprise governance scenario
Before you start
NCBAI, or familiarity with generative AI, recommended; experienced leaders may join directly

About the course

A programme for designing and running enterprise AI governance and risk management. It goes beyond policy to cover the full AI lifecycle: generative AI, RAG, third-party models, autonomous agents, agent identity, MCP and A2A, assurance, incidents and board oversight. Aligned with NIST AI RMF, ISO/IEC 42001, India's AI governance context and the EU AI Act.

What you become

An AI governance professional who can build an enterprise AI governance model and report on AI risk to the board.

Who it is for

  • CISOs, CIOs, CTOs and technology leaders
  • Risk, compliance and internal audit teams
  • Privacy, legal and responsible-AI professionals
  • Security and enterprise architects
  • AI, data, product and platform leaders
  • Consultants and board advisers

Curriculum

  1. Enterprise AI governance and accountability

    Lifecycle, shadow AI, AI inventory, ownership, policy

    The AI, generative and agentic lifecycle; shadow AI and build-buy-consume decisions; AI inventory, criticality tiers and use-case intake; the governance committee, ownership, RACI and policy hierarchy.

  2. AI risk, standards and regulation

    NIST AI RMF, ISO/IEC 42001, DPDP, EU AI Act

    Business, model, data, privacy, cyber and safety risk; third-party and supply-chain risk; NIST AI RMF and its GenAI Profile, ISO/IEC 42001; India's AI governance and DPDP, and the EU AI Act.

  3. Governing GenAI, RAG and agents

    Vendor due diligence, provenance, agent autonomy and kill controls

    Foundation-model and vendor due diligence; RAG, training and fine-tuning governance; model provenance, evaluation and change control; agent autonomy, non-human identity, MCP and A2A, delegated permissions and kill controls.

  4. Assurance, incidents and board oversight

    Testing, monitoring, incidents, board dashboards

    Testing, evaluation, red-teaming and control validation; continuous monitoring and drift; AI incident classification and escalation; board dashboards, KRIs and KPIs, maturity and a roadmap.

What is included

  • Live weekend sessions
  • A case-based enterprise AI governance scenario

Enrol

Send an enquiry to the Cybersecurity & AI Initiative from this page.