Fast Facts

• AI adoption in business is accelerating, raising both opportunity and risk.
• Rigid “ban first” policies often fail, leading to shadow AI use and security blind spots.
• Effective governance requires ongoing adaptation, not static rulebooks.
• Cross-functional teams and tools like AI Bills of Materials help track and secure AI systems.
• Market and regulatory pressures are pushing organizations to get AI governance right - or risk falling behind.

Inside the New AI Wild West

Imagine a gold rush where the gold can think, learn, and - if mishandled - leak your company’s secrets. That’s the landscape facing Chief Information Security Officers (CISOs) as AI tools flood the workplace. With the launch of ChatGPT in late 2022, employees began experimenting with generative AI at breakneck speed, outpacing the cautious policies drafted by security teams. The result? A tug-of-war between innovation and risk, with CISOs caught in the crossfire.

The Policy Trap and Its Pitfalls

History is rife with examples of technology outpacing governance. From the early days of the internet to the rise of cloud computing, organizations that relied on blanket bans or outdated playbooks often found themselves bypassed by employees seeking faster, easier tools. In cybersecurity circles, this is known as “shadow IT” - and now, “shadow AI” is the latest frontier. According to Gartner, by 2025, over half of organizations will have encountered unauthorized AI usage, exposing them to compliance and data leakage risks.

When policies are too rigid, they become handcuffs - ignored in practice and impossible to enforce. The real danger: security teams end up policing the impossible while real threats slip through the cracks.

Building Living Guardrails, Not Walls

So what works? The most effective CISOs are treating AI governance as a living, breathing system. Tools like an AI Bill of Materials (AIBOM) provide a map of what data and algorithms are in play, similar to how ingredient lists reveal what’s in our food. Model registries act like maintenance logs, tracking which AI systems are running, when they were updated, and how they’re performing.

But technology alone isn’t enough. Cross-functional committees - bringing together legal, HR, compliance, and business leaders - ensure that governance isn’t just a security edict but a shared mission. This bridges the gap between business goals and risk management, turning the security team from the “department of no” into an enabler of innovation.

Why the Stakes Are Higher Than Ever

With regulators scrutinizing AI’s impact on privacy and fairness, and markets rewarding companies that harness AI safely, CISOs face more than just technical challenges - they’re navigating a minefield of reputational and legal risks. The SANS Institute’s Secure AI Blueprint urges leaders not just to protect AI, but to use it to bolster their own defenses. The best governance programs don’t just keep AI safe; they make security a competitive advantage.

WIKICROOK

• AI Bill of Materials (AIBOM): An AI Bill of Materials (AIBOM) lists all data, software, and services used in an AI system to help organizations identify and manage risks.
• Shadow AI: Shadow AI is when employees use AI tools without official approval, creating hidden security and compliance risks for organizations.
• Model Registry: A model registry is a system for tracking AI models, their versions, updates, and performance, supporting safe maintenance and risk management.
• Cross: Cross-Site Scripting (XSS) is a cyberattack where hackers inject malicious code into websites to steal user data or hijack sessions.
• Governance Policy: A governance policy is an organization’s set of rules and guidelines for safely managing and using technology, data, and resources.