New Year Offer End Date: 30th April 2024
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Program

AI Governance & Risk Management (AI GRC)

Master AI Governance and Risk Management to Safeguard Innovation and Compliance.

Skills you will gain:

About Program:

This 5-day hands-on workshop is designed for professionals seeking to understand and implement AI Governance & Risk Management (GRC) frameworks. Participants will learn to identify, classify, and mitigate AI risks while balancing ethical, legal, and regulatory compliance requirements. Through case studies, exercises, and practical templates, they will gain the skills to build AI governance programs, handle AI security and privacy concerns, and communicate AI risk at the board level.

Aim: To provide participants with a comprehensive understanding of AI governance, risk management frameworks, security, privacy controls, compliance, and how to effectively implement AI GRC practices in organizations.

Program Objectives:

  • Understand the key aspects of AI governance, risk management, and how AI differs from traditional IT risk.
  • Classify and assess various AI risks, including strategic, ethical, privacy, security, and legal risks.
  • Learn about AI security risks and develop control frameworks to manage them effectively.
  • Understand AI regulations, ethics, bias mitigation, and responsible AI principles.
  • Develop AI governance frameworks and report AI risks to senior management and boards.
  • Create an AI Governance Plan and integrate it with enterprise GRC tools.

What you will learn?

📅 DAY 1 – Foundations of AI Governance

  • Evolution of AI: GenAI to Autonomous AI
  • AI vs traditional IT risk and real incidents (bias, hallucinations, misuse)
  • AI as a business risk multiplier
  • Case Discussion: AI hiring bias / GenAI data leakage
  • Defining AI Governance: People, Process, Technology
  • Key stakeholders: Board, CISO/CIO, Legal, Business Owners, CAIO
  • Activity: Identify AI systems in organizations

📅 DAY 2 – AI Risk Management Frameworks

  • Risk Categories: Strategic, Ethical, Privacy, Security, Legal, Operational
  • Exercise: AI Risk Brainstorming (Chatbots / Copilot)
  • Risk Assessment Lifecycle: Identification, scoring, ownership, mitigation, monitoring
  • Template: AI Risk Register walkthrough

📅 DAY 3 – AI Security, Privacy & Control Mapping

  • Security Risks: Prompt Injection, Data leakage, Model drift, Shadow AI, Third-party risks
  • Demo: Prompt injection in action
  • Control Mapping: ISO 27001, NIST AI RMF, COBIT, Human-in-the-loop, Logging, Audit trails
  • Workshop: Map AI risks to controls

📅 DAY 4 – Compliance, Ethics & Regulation

  • Regulations: EU AI Act, India’s AI direction, GDPR, ISO/IEC 42001, Sectoral regulations
  • Discussion: Regulated vs Non-Regulated AI use cases
  • Ethics & Responsible AI: Fairness, transparency, bias mitigation, ethical review boards
  • Scenario: Accountability in AI-driven decisions

📅 DAY 5 – AI GRC Implementation & Board Reporting

  • Building an AI Governance Program: Operating model, policies, risk committees, integration with GRC tools
  • Deliverable: AI Governance Framework Blueprint
  • Board-Level Communication: Explaining AI risk to non-technical leaders, AI risk dashboards, Incident response
  • Capstone: Design an AI Governance Plan for a fictional company

Mentor Profile

Cyber and Cloud Security Trainer NIIT Foundation
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Fee Plan

INR 1999 /- OR USD 50

Get an e-Certificate of Participation!

2024Certfiacte

Intended For :

  • Professionals in AI, IT, cybersecurity, legal, compliance, and governance roles.
  • Managers, executives, or anyone responsible for managing AI risks, ethics, or security within their organizations.
  • Basic knowledge of AI or IT governance is helpful but not required.

Career Supporting Skills

Program Outcomes

  • Define and implement AI governance practices, including stakeholder roles (CISO, CAIO, Legal).
  • Identify and categorize AI risks and implement effective risk mitigation strategies.
  • Map AI risks to security and control frameworks like ISO 27001, NIST, and COBIT.
  • Comprehend AI regulations, standards, and ethical principles, and apply them to various AI use cases.
  • Build and present an AI Governance Framework tailored to their organization’s needs.
  • Communicate AI risk and governance strategies effectively to non-technical leaders and boards.