One of Its key policy areas, Human Oversight & Accountability (Annex A.3), emphasises AI must always remain under control, given how advanced technology becomes.

Why Human Oversight Matters

AI brings speed, consistency, and scalability, no doubt. Yet, it can also be prone to too many risks if left unchecked. As reiterated in our previous blog contents, it can make biased decisions, act unpredictably, or operate in ways that don’t align with ethical or legal expectations.

Human oversight ensures that AI remains a tool, not a decision-maker in isolation. It allows organizations to step in, review, and correct its course when needed. In short, it keeps accountability where it belongs with people.

Defining Accountability in Practice

ISO/IEC 42001 calls for organizations to define clear roles and decision rights for every AI system.

• Who owns the model?
• Who signs off before deployment?
• Who steps in if something goes wrong?

Some companies have addressed this by creating AI governance committees or assigning roles such as an AI Ethics Officer or Responsible AI Lead. Others require high-risk models, such as those affecting credit decisions, medical recommendations, or even receiving legal or compliance approval before they go live.

Keeping Humans in the Loop

If an AI recommends a loan denial or a medical diagnosis, for example, the policy may require that a qualified professional reviews and approves the decision before action is taken.

This human-in-the-loop approach ensures that AI supports human judgment, rather than replace it.

Building Traceability and Trust

True accountability means being able to trace how and why an AI made a decision.

That's why the standard promotes auditability and traceability, keeping detailed logs of model inputs, outputs, versions, and approvals.

Organizations are now using tools like Databricks Model Monitor and Fiddler AI to detect unusual model behavior, while frameworks such as Model Cards or Algorithmic Impact Assessments (AIA) help document who built the model, its intended purpose, and its limitations.

When something goes wrong, these records make it clear who is responsible and what needs to be fixed.

Global Alignment on Responsible AI

The OECD AI Principles highlight that humans must retain the capacity for agency and oversight over AI systems.

ISO/IEC 42001 brings this to life by requiring that every high-risk AI system has a designated human overseer, someone with the authority and understanding to intervene, explain, and take responsibility.

Final Thoughts

At its core, AI governance is not just about technology, it's about trust.

ISO/IEC 42001 reminds us that accountability doesn't scale with automation; it scales with people.

By embedding human oversight into every step of the AI lifecycle, organizations can ensure their innovations remain ethical, transparent, and controllable, even as automation accelerates.

No matter how intelligent our systems become, responsibility must always remain human.