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Foundations of AI Governance in Management Systems

Module 1: What AI governance means for this audience

The Architecture of an AIMS

Context of the Organization

Leadership, Roles, and the AI Lifecycle

Module 2: Where quality and compliance managers fit in

Leadership

AI System Lifecycle Management

Word Search

Managing AI Risks, Controls, and Incidents

AI Risk Assessment

AI Risk Treatment and Control Measures

Incident Management and Response

Performance Evaluation and Integration

Module 3: Integrating AI governance into existing systems

Performance Evaluation

Implementation Strategy

Suggested Implementation Roadmap

Quiz

4.3 Determining the Scope of the AIMS

5.3 Organizational Roles, Responsibilities and Authorities

8.1 Operational Planning and Control

9.2 Internal Audit

10. Improvement

Course Feedback

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Artificial Intelligence is rapidly transforming the business landscape, bringing unprecedented opportunities alongside complex new risks. For Quality, Compliance, and HSQE Managers, the challenge is no longer just understanding AI—it's governing it.

$ (USD)

Artificial Intelligence is rapidly transforming the business landscape, bringing unprecedented opportunities alongside complex new risks. For Quality, Compliance, and HSQE Managers, the challenge is no longer just understanding AI—it's governing it. Welcome to "ISO/IEC 42001: AI Governance for Quality and Compliance Managers," a comprehensive course designed to bridge the gap between technical AI development and formal management system compliance.

This course demystifies AI governance by framing it not as a purely technical engineering challenge, but as a structured management system issue. You will explore the core components of the ISO/IEC 42001 Artificial Intelligence Management System (AIMS) and learn how it seamlessly integrates with familiar frameworks like ISO 9001 and ISO 27001. Throughout the modules, we will guide you through the entire AI lifecycle, from defining the context of your organization and establishing leadership roles to conducting rigorous AI risk assessments and implementing robust control measures.

You will discover how to translate high-level AI policies into actionable, auditable controls, manage AI-related incidents using established quality management practices, and evaluate the ongoing performance of your AI systems. Whether you are looking to extend your current third-party oversight to AI vendors or preparing your organization for formal certification, this course provides a practical, step-by-step implementation roadmap. Equip yourself with the skills to lead your organization's AI governance strategy and ensure that your AI deployments are ethical, compliant, and continuously improving. Join us to turn AI risks into governed, structured processes.

ISO/IEC 42001 - AI Governance for Quality and Compliance Managers

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            <p>Artificial intelligence is rapidly transforming how organizations operate, but for those of us managing quality, compliance, and risk, it introduces a whole new layer of complexity. You already know how to navigate established frameworks like ISO 9001, ISO 27001, or ISO 22301, but AI isn't just another software update—it requires a structured, governed approach. That's exactly where ISO/IEC 42001 comes into play. This standard shifts AI from being a purely technical engineering challenge into a formal management system issue. It allows you to leverage your existing expertise in risk assessment, policy integration, and continuous improvement to bring AI applications under control, ensuring they are safe, ethical, and compliant.</p>

<p>Throughout this course, we will break down the core components of the Artificial Intelligence Management System (AIMS) and show you exactly where you fit into the AI lifecycle. We'll explore how to determine the context of your organization, secure leadership commitment, and apply standard quality management controls to AI risks like algorithmic bias and data privacy. You'll also discover practical strategies for integrating AI governance seamlessly into your current management systems, handling AI-specific incidents, and evaluating performance. By the end, you will have a clear, actionable roadmap to implement ISO/IEC 42001, turning high-level AI policies into auditable controls without needing to become an AI software engineer.</p>
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