Has Anyone Else Found AI Risk Assessment and Governance Difficult While Preparing for the ISO/IEC 42001 Foundation Exam?
Currently, I have been studying for the ISO/IEC 42001 Foundation examination. Honestly speaking, some AI governance ideas require more time to be understood than I thought before. Initially, I believed that the most difficult thing would be learning the terminology used in the standard, however, it appears more challenging to understand the application of the standard's requirements to practice. AI risk assessment seems to be particularly tricky. I understand that the organization should assess risks related to AI, but at times, it is hard for me to understand the process of risk treatment, monitoring and continuous improvement within the context of the whole AI management system. Learning the difference between risks in AI and the organization's responsibilities in dealing with such risks was not easy either. I have started using ISO IEC 42001 Foundation practice questions to check whether I can apply what I have studied rather than simply recognise familiar terms. Some scenario-based questions make me stop and think because more than one option can initially seem reasonable. Reviewing why an answer is appropriate has been more useful than just trying to remember it. I am particularly interested in how others approach the relationship between AI governance, risk management, and organisational controls.
Has anyone who has taken this exam experienced similar difficulties? Which topics would you recommend spending more time on, especially when it comes to understanding practical AI management situations?
Yes, I faced similar difficulties, particularly with the difference between AI risk assessment and risk treatment. My advice is to focus on Clause 6 (Planning) and Clause 8 (Operation). Understand how risks are identified, evaluated, treated, and monitored rather than memorizing definitions. Also, pay attention to the roles of human oversight, accountability, and organizational controls. These areas make more sense when you connect them with practical AI scenarios. That approach helped me understand the questions much better.