The AI Governance Gap: Why CISOs Can’t Afford to Stay on the Sidelines

By Mike Gentile, CEO of CISOSHARE

Your employees are already using generative AI. Chances are, you just don’t know how, where, or with what data. 

It’s the biggest unauthorized tech rollout in enterprise history, and if you’re a CISO watching from the sidelines, you’re likely in the blast radius.

From marketing to software development to customer support, AI is reshaping how work gets done. While most of the conversation centers on innovation, automation, and cost savings, one question keeps getting pushed aside: 

Who is actually governing these systems? The uncomfortable truth is that in many organizations, no one is.

According to a recent Gartner survey, 55% of enterprises are actively piloting or using generative AI tools. However, fewer than 10% have implemented any formal AI governance. In the rush to operationalize the benefits, security and accountability have taken a back seat. 

That needs to change, and Chief Information Security Officers (CISOs) are strongly positioned to drive that change. Let’s talk about it. 

Why the CISO Should Lead AI Governance

Traditionally, AI governance has been thought of as a task for data science, legal, or compliance teams. However, generative AI introduces a different level of risk that intersects with the very foundations of information security.

When AI tools are deployed without clear oversight, they can introduce exposure in unexpected ways:

• Sensitive data can leak into training models.
• Shadow IT can proliferate with unsanctioned tool adoption.
• Outputs can reflect unintended bias or hallucinated information, damaging reputations.
• Regulatory violations can occur if compliance isn’t baked into how these tools are used.
  

These concerns are real, operational, and already impacting organizations, and in most cases, they fall squarely within the domain of the CISO.

Security leaders are already fluent in identifying risk, developing policies, and ensuring technical controls are applied across systems. That makes them natural candidates to take the lead in shaping how generative AI tools are evaluated, deployed, and monitored.

AI Without Guardrails Is a Trust Problem

AI adoption isn’t slowing down, but in the absence of clear governance, every new integration introduces questions around trust. Can we verify the integrity of the output? Who’s accountable if things go wrong? Is this system reinforcing or undermining our security posture?

CISOs can’t afford to sit this one out. Without their input, decisions around AI usage risk being made by default rather than design.

A good starting point for any CISO evaluating AI use cases is to ask:

• What data is being fed into this model? Is it sensitive? Can it be reversed or extracted?
• Where is the model running? Are we using a secure and compliant environment?
• Who is responsible for monitoring outputs and auditing usage?
• Are there policies in place governing acceptable use, training data, and integration protocols?

These are basic questions, but the truth is, they’re often overlooked in the excitement of adoption.

What AI Governance Looks Like in Practice

Governance doesn’t need to be a bottleneck. In fact, when done right, it can become a framework that enables AI innovation while reducing exposure. Some CISOs are already taking steps such as:

• Understanding the basics: what data you have, where it is located, and how it is used.
• Establishing cross-functional AI governance boards that include security, legal, data science, and business stakeholders.
• Drafting acceptable use policies that cover internal and third-party AI tools.
• Embedding risk assessments for AI models into existing security review processes.
• Creating incident response playbooks for AI-specific failures, such as misinformation, leakage, or bias.
  

Most of these measures build on capabilities CISOs already oversee. The challenge is elevating them to match the scale and pace of generative AI adoption.

From Gatekeeper to Guide: Redefining the CISO Role

The rise of AI presents a rare moment for CISOs to expand their influence beyond technical operations and into enterprise strategy.

In many organizations, AI is being adopted from the top down, with executive leadership eager to capture its benefits. That means security professionals have a seat at the table, if they’re willing to claim it.

You don’t need to be a data scientist or AI engineer to lead in this space. What’s needed now is deep expertise in governance, control, and risk; areas where CISOs already operate with authority.

AI will shape the future of business, but without security at its core, it’s a future built on unstable ground. The tools gaining traction today have the potential to become tomorrow’s biggest vulnerabilities if no one takes ownership now.

About the Author:

Mike Gentile is CEO of CISOSHARE, a cybersecurity program development firm that works with some of the world’s most complex organizations.

He has more than 20 years of experience designing and implementing enterprise security programs.