Most organisations are already running AI. The question isn’t whether it needs to be governed; it’s whether anyone is actually governing it.
AI and automation move faster than traditional audit cycles can handle. They introduce risks that don’t look like the ones we were trained to spot: models drifting silently, automated workflows making decisions at scale before issues are noticed, and accountability gaps that only surface when something goes wrong.
In this one-hour ISACA SheLeadsTech webinar, Ravneet Kaur will share practical ways to make AI governance doable, not just desirable. Drawing on her experience at the intersection of technology, cybersecurity, delivery and governance, she will unpack the frameworks, language and starting points that help organisations move from uncertainty to structured oversight.
What you’ll take away:
• Why AI and automation challenge traditional governance models.
• A simple two-domain risk taxonomy you can start using immediately.
• How to extend familiar frameworks such as NIST AI RMF, COBIT and OWASP LLM Top 10.
• Practical assurance approaches, including continuous monitoring, bias detection and human-in-the-loop oversight.
• Three actions you can take this week using tools you already have.
Why now: AI governance isn’t a future problem. If your organisation has deployed AI or automation, and it almost certainly has, the oversight gap exists.