AI adoption is moving faster than most security programmes can keep up with.
Employees are using AI tools. Business teams are integrating AI into workflows. Developers are connecting third-party models and APIs. Sensitive information is increasingly moving through systems that security teams may never have formally assessed.
The result is a growing gap between what the organisation is doing with AI and what security actually knows about it.
In Episode 4, we explore the AI governance gap and why visibility may be one of the biggest enterprise security challenges of the AI era.
We examine:
• Shadow AI and unsanctioned AI adoption
• AI-driven data leakage and prompt exposure
• Third-party AI integrations and emerging trust boundaries
• AI vendor assessments and security due diligence
• Model governance and accountability
• Data residency and regulatory considerations
• The role of AI risk committees
• Why governance cannot become a barrier to innovation
• How security leaders can regain visibility without slowing the business
The challenge isn't simply deciding which AI tools employees are allowed to use.
The harder question is whether security leaders understand where AI is being used, what data is entering these systems, who has access, what decisions are being made, and what happens downstream.
AI governance is becoming an enterprise visibility problem—and ultimately, a trust problem.
Connect with me on LinkedIn for additional insights and ongoing discussions:
www.linkedin.com/in/oliviaabibayo
For speaking engagements, advisory opportunities, partnerships, or general enquiries:
📧 security@thevirtualciso.ca
Thank you for listening to The Virtual CISO.
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