The Cost of AI Risk: What CISOs Should Prepare For

Maya Rosenstein
Sep 3
4 min read

Updated: Oct 23

By: Itai Sassoon, Commugen CEO

The Unseen Price of AI Risk

Every CISO I’ve spoken to in the past year says, "Even with the strongest processes and the sharpest teams, it will find its way in.”

They’re not talking about ransomware, nation-state hackers, or insider risk.

They’re talking about AI, and the risk it creates.

Employees are embedding ChatGPT, Gemini, and Copilot into their workflows. While the benefits are visible - faster drafts, quicker responses, streamlined processes - the risks quietly accumulate beneath the surface. Don’t get me wrong - automation and AI usage are business imperatives today. Smart business leaders are utilizing those benefits while limiting the risks.

From compliance gaps to reputational exposure, AI Risk, and specifically Shadow AI isn't just a risk, it’s a hidden cost center.

This blog explores the costs and why IT and cyber GRC leaders must account for them before they multiply.

Download our full playbook:

5 Steps to Mitigate AI Risk

What Is Shadow AI?

Shadow AI involves the unauthorized use of generative AI tools within organizations, often without formal oversight. AI tools are frequently embedded invisibly into browser extensions, Slack chats, and daily workflows.

Shadow AI and AI risks in general are not driven by malice; they are driven by momentum. Employees seek to be quicker, more effective, and more efficient, and they turn to AI to achieve this. We should enable this, while managing the risk intelligently.

Understanding the costs of AI risk is crucial because organizations must realize that even "innocent” AI use can pose significant financial and cyber threats. Once the connection between cyber risk and long-term costs is clear, it becomes much easier to help organizations prepare for and reduce AI risk.

The Cost Categories of AI Risk

“The real price is not the fine you pay, but the cost of cleaning up the mess after.”

- CISO, Fortune 500 Bank

1. Regulatory Exposure

Risk Scenario:

An employee uses an unapproved AI tool to process data. Unknowingly, this data includes personal or regulated data, triggering potential violations under GDPR (lack of consent/audit trails), HIPAA (exposure of PHI), or the EU AI Act (misuse of high-risk systems).

Cost Impact: Fines, mandated remediation plans, and resource-heavy compliance audits.

2. Incident Response & Legal Cleanup

Risk Scenario:

A developer pastes proprietary code into the free version of ChatGPT. Suddenly, when anybody is asking ChatGPT about your company’s tech, the secret sauce comes right up. Legal, privacy, and security teams spend weeks trying to untangle the breach.

Cost Impact: Outside counsel fees, incident investigation costs, and diverted team capacity.

3. Vendor Risk & Supply Chain Complexity

Risk Scenario:

GenAI plugins and AI features are embedded in trusted tools like Notion or Slack, often bypassing formal third-party reviews. Even if the base platform has passed vendor vetting, these embedded AI features can process sensitive data in ways outside the original approval scope.

Cost Impact: Contract renegotiations, emergency vendor reassessments, and reputational harm if a partner’s AI component is compromised.

4. Ethical & Decision Risk

Risk Scenario:

Unverified AI outputs can influence decisions, especially in public or strategic contexts. Hallucinations, bias, or lack of explainability lead to ethical lapses and trust breakdowns.

Cost Impact: Strategic missteps, loss of stakeholder trust, and public relations & reputational damage.

5. Control & Remediation Debt

Risk Scenario:

AI embeds quietly into daily workflows, normalizing unsanctioned use before the IT team can react. The longer governance is delayed, the harder and costlier it becomes to unwind entrenched risky patterns.

Cost Impact: Higher remediation costs, longer change-management cycles, strained IT and compliance resources, and lost opportunity from delaying safe, sanctioned AI adoption.

Why AI Risk Costs Go Unnoticed

Most organizations don’t take “informal AI use” into budget considerations. Why?

Because it doesn’t show up in budgets, no licenses, contracts, or purchase records exist.

But these hidden costs manifest elsewhere:

In audit delays
In customer trust erosion, and even churn
In remediation efforts
In cross-functional firefighting from Legal, Security, and IT

AI Risk is a budget risk disguised as a productivity hack.

How Can CISOs Control AI Usage Without Blocking Innovation?

CISOs must evolve from AI enforcers to AI enablers. Here’s how:

Map AI Behavior: Start with employee awareness and surveys that classify AI usage by sensitivity, purpose, and exposure..
Implement Tiered Controls: High-risk AI usage? Block or migrate. Low-risk? Allow and monitor.
Automate Governance: Manual processes can’t scale. Look for platforms that embed controls into workflows, not just documents.

👉 Our AI Governance Guide shows exactly how to do this.

Final Thoughts: Cost Avoidance Is ROI

It’s tempting to delay AI governance in the name of “not being ready.”

But costs accrue whether you act or not.

Governing AI is not about restriction but resilience. When CISOs take a proactive, cost-aware approach, they reduce risk and unlock safe, scalable innovation.