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AI Governance Risk and Compliance

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AI Governance Risk and Compliance

I4023

London (UK)

26 Oct 2026 -30 Oct 2026

5830 €

Overview

Introduction:

Artificial intelligence governance, risk, and compliance (AI GRC) is a strategic discipline that ensures the responsible, secure, and compliant development, deployment, and oversight of AI systems across organizational environments. It integrates AI governance, risk management, regulatory compliance, ethics, data governance, cybersecurity, and organizational accountability to support trustworthy and sustainable AI adoption. This training program explores AI governance frameworks, risk management methodologies, regulatory compliance models, ethical AI principles, and assurance practices that strengthen organizational control over AI technologies. It provides an institutional perspective on how AI governance, risk, and compliance enhance transparency, mitigate AI related risks, ensure regulatory alignment, and support responsible AI innovation.

Program Objectives:

By the end of this program, participants will be able to:

  • Analyze AI governance frameworks and organizational oversight models.

  • Evaluate AI risk management and regulatory compliance approaches.

  • Assess ethical AI, data governance, and accountability frameworks.

  • Examine AI assurance, monitoring, and organizational control mechanisms.

  • Explore governance practices that strengthen responsible and trustworthy AI adoption.

Target Audience:

  • AI Governance and Risk Professionals.

  • Compliance and Regulatory Officers.

  • Information Security and Cybersecurity Professionals.

  • Data Governance and Privacy Specialists.

  • Technology, Risk, and Audit Managers.

Program Outline:

Unit 1:

Foundations of AI Governance:

  • AI governance principles.

  • Organizational governance frameworks for AI.

  • AI lifecycle governance models.

  • Roles and responsibilities in AI governance.

  • AI governance standards and guidelines.

Unit 2:

AI Risk Management:

  • AI risk management frameworks.

  • AI risk identification and classification.

  • AI model risk management.

  • Operational and strategic AI risks.

  • AI risk assessment methodologies.

Unit 3:

AI Compliance Ethics and Data Governance:

  • Regulatory compliance frameworks for AI.

  • Ethical AI principles.

  • Data governance and data quality frameworks.

  • Privacy and data protection requirements.

  • Accountability and transparency models.

Unit 4:

AI Assurance Monitoring and Control:

  • AI assurance frameworks.

  • AI performance and monitoring models.

  • AI audit and validation methodologies.

  • AI control and oversight mechanisms.

  • AI incident management frameworks.

Unit 5:

Enterprise AI Governance and Responsible AI:

  • Enterprise AI governance strategies.

  • Responsible AI implementation frameworks.

  • AI governance maturity models.

  • Continuous compliance and governance improvement.

  • Organizational trust and AI resilience frameworks.