Let’s face it—AI is no longer just a buzzword. It’s already here, and it’s changing how organizations operate, regardless of size or sector. From chatbots handling customer queries to complex algorithms supporting decision-making, artificial intelligence has quietly made its way into our day-to-day business functions.

But here’s the catch: while AI brings efficiency and innovation, it also brings along new and unique risks. And this is exactly why, as auditors or risk professionals, we can’t afford to overlook AI risk when we review an organization’s risk register.

During a recent audit, I noticed something interesting—while the risk register did a good job covering typical areas like entity-level risks, IT risks, and operational risks, it was silent on AI although the organization has made massive investment in AI. That raised a red flag. If an organization is using AI—even in a limited capacity—we need to ensure its associated risks are formally recognized, documented, and managed.

So, what should auditor be looking for?

When reviewing AI risk, it’s important to first understand how and where AI is being used. Is it automating decisions? Processing sensitive customer data? Supporting internal analysis? Once we know that, we can begin to ask the right questions:

• Are the AI tools used by the organization aligned with responsible AI principles?
• Have roles and responsibilities with respect to use and managing AI been clearly defined?
• Are we sure the AI’s output doesn’t compromise the confidentiality, integrity, or availability of data?

Here are a few key areas to consider while reviewing or updating the risk register:

1. Transparency and Accountability – Does the organization have clear visibility into how AI models operate and make decisions?
2. Governance and Leadership – Is there a structure in place to oversee AI usage responsibly?
3. Access Controls – Are safeguards in place to protect AI systems and the data they use?
4. Data Integrity Threats – What defences are in place to prevent issues like data poisoning or adversarial machine learning?
5. Audit Trails – Are AI decisions traceable with proper documentation?
6. CIA Impact – How do AI systems affect the confidentiality, integrity, and availability of information?
7. Generative AI Risks – Is the team prepared to handle challenges like hallucinations in AI-generated content?
8. Third-Party Vendors – Are external AI tools compliant with internal policies and legal requirements?

Wrapping It Up

The bottom line is this: AI risk isn’t just an IT issue—it’s a business risk. If your organization is using AI, even in a small way, those risks need to be on the radar and in the risk register. As auditors, our role is to help organizations not just identify these risks but build the right governance around them.

By making AI risk a formal part of risk discussions, we help ensure that innovation doesn’t outpace responsibility. And in today’s rapidly evolving digital world, that balance is more important than ever.