AI Risk Management

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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