AI Risk Management

Course Category : Risk Management

A professional training programme focused on identifying, assessing, and managing AI risks to ensure secure, trustworthy, and compliant AI implementation across organisations.
Duration: 5 Days
Level: Advanced

Introduction

Artificial intelligence is transforming organisations across every sector; however, its adoption introduces technical, operational, legal, ethical, and strategic risks that can significantly affect organisational performance and stakeholder trust. Effective AI risk management has therefore become a critical capability for ensuring responsible AI adoption and regulatory compliance.
This course provides a comprehensive framework for AI risk management, covering risk identification, assessment, mitigation, governance, monitoring, and continuous improvement in alignment with internationally recognised standards and enterprise risk management principles..

Targeted Audience

Executives.
AI and Digital Transformation Managers.
Enterprise Risk Managers.
Governance and Compliance Officers.
IT and Cybersecurity Managers.
AI and Data Science Teams.
Internal Auditors.
Technology and Legal Consultants.

Targeted Skills

AI Risk Identification.
Risk Assessment and Analysis.
AI Risk Management Frameworks.
Risk Control Design.
AI Governance.
Continuous Risk Monitoring.

Expected Outcomes

Understand international AI risk management principles.
Identify and classify AI-related technical, regulatory, and ethical risks.
Design an enterprise AI risk management framework.
Develop effective mitigation and compliance controls.
Integrate risk management throughout the AI lifecycle.
Strengthen trust and resilience in AI-enabled organisations.

Training Topics Index

Understanding AI risks.
AI risk lifecycle.
Risk management and governance.
International AI risk standards.
Organisational responsibilities.

Internal and external risk sources.
Risk likelihood and impact assessment.
Data, model, and algorithm risks.
Legal and regulatory risks.
Risk prioritisation.

Risk treatment strategies.
Preventive, detective, and corrective controls.
Bias and explainability management.
Privacy and security risk controls.
Risk documentation.

AI risk governance structure.
Key Risk Indicators (KRIs).
Continuous monitoring and reporting.
Internal audit and assurance.
Policy and regulatory compliance.

Enterprise AI risk strategy.
Risk integration across AI projects.
AI incident response.
Continuous improvement.
Global best practices.

Course Features

Updated and Interactive Content
Hypothetical Examples and Case Studies
Pre- and Post-assessments to Measure Impact
Verified Certificate with a QR Verification Code

AI Risk Management