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ISO 42001 Decoded: AI Governance & Risk in Practice
Rating: 4.0 out of 5(6 ratings)
95 students

ISO 42001 Decoded: AI Governance & Risk in Practice

ISO Certification May Be Optional But Governance is Not | Manage AI Risks Smartly | With Practical Examples
Created bySeaportAi .
Last updated 4/2026
English

What you'll learn

  • What is ISO 42001
  • Why we need ISO 42001
  • What are the other ISO standards that influence AI deployment
  • What are the AI lifecycle processes
  • What are the steps in ML pipeline that align with AI lifecycle processes
  • What are the best practices in managing risks in AI deployment
  • What are the guidelines to reduce bias in AI systems
  • What are the best practices to improve the robustness of neural networks
  • What are the building blocks of AI governance, as per ISO standards

Course content

7 sections22 lectures1h 51m total length
  • Setting the context5:12
  • Management System Standard2:26

    ISO 42001 decodes the management system standard framework for AI governance and risk, outlining structured steps, risk assessment, and continuous improvement with leadership and employee engagement.

  • AI Refresher: What We Are Actually Governing4:48

Requirements

  • Knowledge and/or experience in machine learning and artificial intelligence will be significantly advantageous.

Description

AI governance is no longer a theoretical discussion or a compliance checkbox. As organizations accelerate AI adoption, risks are quietly embedding themselves into everyday decisions. Models drift, outputs lose grounding, bias creeps in, and yet everything appears to be working. This is where most organizations get it wrong. They have policies, but those policies do not influence behavior. They document intent, but do not control outcomes.

ISO 42001 is the first ISO standard defining a certifiable management system for AI. It provides organizations with a credible mark of trustworthiness in how AI is designed, deployed, and governed. In a world where enterprises are actively seeking ways to make AI reliable and scalable, this standard becomes a powerful enabler of commercial growth. More importantly, it shifts the conversation from isolated AI initiatives to organization-wide responsibility, offering a structured framework for implementing effective AI governance and management systems.


This program is designed to close that gap. It is not about memorizing clauses or understanding the standard at a surface level. It is about translating ISO 42001 into practical, executable governance. You will learn how to move from static documents to dynamic control systems. From risk identification to risk management that is measured, monitored, and actively managed.


Through real-world scenarios, you will explore how AI risks hide in plain sight and how to bring them under control. You will learn what should be measured, what is typically measured, and how to go beyond that using techniques such as drift detection, bias and fairness evaluation, and stability of model explanations. More importantly, you will understand how to embed these controls into workflows so that governance is not an afterthought but part of everyday decision-making.

Even if you are not pursuing ISO 42001 certification, the principles in this program remain critical. AI governance is not about certification, it is about control, accountability, and trust in how AI is used across the organization.


By the end of this program, you will not just understand ISO 42001. You will know how to make it work.

Disclaimer:

This training material is an independent educational resource based on a general interpretation of ISO 42001 principles. It is not an official publication and is neither affiliated with, endorsed by, nor certified by the International Organization for Standardization or the International Electrotechnical Commission.

ISO 42001 and related standards should be referred to only through official publications issued by ISO. ISO, ISO/IEC, and all associated names, acronyms, and marks are the intellectual property of ISO and IEC. Any references made in this material are for informational purposes only and do not imply any formal association or approval.

Who this course is for:

  • CxO's
  • Senior Managers
  • IT Professionals
  • Machine Learning enthusiasts
  • Data Science professionals
  • Students