The Urgency of Securing AI Agents—From Shadow AI to Governance

The Rise of Shadow AI

Every CISO has lived through shadow IT, the era when employees swiped their credit cards for SaaS apps outside IT’s control. Now, a new technology is rapidly spreading that is often outside the control of security and IT teams: shadow AI.

Recent CISO focus group conversations we conducted revealed this pattern. Employees are adopting AI copilots for coding, agents for productivity, and orchestration servers for experimentation, often without security’s knowledge. Developers test new workflows. Business teams subscribe to niche AI services. Security teams themselves deploy AI-powered tools. The result is an invisible footprint of AI agents woven throughout the enterprise.

In one Fortune 500 company, a discovery process revealed over 6,000 agent-linked identities created in just two months. Security, IT, and operations leaders were shocked. They didn’t know those agents existed, let alone what data they were accessing.

This is the new normal. And without intervention, it is a recipe for risk.

Why AI Agents Are Different

Shadow IT was about applications. Shadow AI is about actors. Each AI agent is not just a tool - it is an identity that can act in the environment. And unlike traditional automation scripts, agents are goal-driven. They can chain actions, invoke other agents, and make decisions beyond what developers originally scoped. This makes them both powerful and dangerous. They don’t just sit passively. They move, adapt, and act.

The Security Gaps Emerging Today

CISOs surfaced several critical gaps that shadow AI introduces:

1. Unknown Identities: Many organizations don’t even know which agents exist. Without an inventory, visibility is nonexistent.
2. Excessive Privileges: To avoid friction, teams often grant agents broad access. Over time, these “toxic combinations” of privileges create major risk.
3. Compliance Blind Spots: Regulators and auditors expect clarity: who created the agent, what it accessed, whether it respected entitlements. Few companies can produce this evidence today.
4. AI Agent Lifecycle Neglect: Agents are rarely deprovisioned. Once created, they linger indefinitely, becoming zombie assets that waste resources and expand the attack surface.
5. Segregation of Duties: CISOs raised concerns about agents colluding. For example, one AI coding agent writing code and another reviewing it, without human oversight. Segregation of duties, long a principle in governance, must now apply to agents too.
   
   

Why the Urgency Is Real

Business leaders aren’t slowing down AI adoption. Competitive pressure is too great. AI is already being used to speed up customer service, streamline IT, optimize operations, and cut costs. CISOs cannot simply hit pause on these game-changing initiatives.

But waiting for standards to harden or for regulators to dictate requirements is risky. By then, the footprint of uncontrolled AI agents will be too large. Enterprises that don’t act today will find themselves overwhelmed tomorrow by having to manage not dozens, but thousands of agents, each with unclear permissions and ownership.

Governance as the Path Forward

The CISOs in our focus group weren’t calling for bans or moratoriums on AI adoption. They were calling for governance. Specifically, a process-based playbook emerged:

1. Discovery and Visibility: The starting point is knowing what exists. Tools and processes must scan cloud, SaaS, and on-prem environments to identify agent-linked identities.
2. Governance Committees: Several CISOs have already stood up AI governance committees to evaluate proposals, set risk thresholds, and enforce accountability. This creates a forcing function for discipline.
3. Guardrails, Not Roadblocks: Security can’t be the department of “no.” Instead, CISOs are enabling experimentation within guardrails for risk scoring, synthetic data use for low-risk trials, and incremental privileges.
4. AI Agent Lifecycle Management: Define a proper lifecycle for agents. Every agent must have a start date, a documented purpose, an owner, and criteria for deprovisioning.
5. Audit Preparation: Capture lineage and activity logs. Be ready to demonstrate compliance with frameworks like the EU AI Act and ISO 42001.

Creating the Business Case

Why does this matter? Because unchecked agents are not just a technical problem, they are a business risk.

• Compliance: Regulatory fines are real, and regulators are watching AI closely.
• Reputation: Customers expect that AI-powered services are secure and fair. A data exposure caused by an uncontrolled agent could devastate trust.
• Cost: Unmonitored agents drive up infrastructure spend, often without delivering business value.
• Operational Stability: Agents that act unpredictably or worse, in conflict, can disrupt business processes.

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From Chaos to Control

The opportunity is not to stop enterprise AI adoption. It is to foster innovations safely and securely. CISOs must be the ones who transform shadow AI into structured AI, providing the guardrails that allow innovation without chaos.

One participant summed it up: “The risks aren’t stopping us from adopting agents, but they are things we need to get ahead of before adoption scales further.”

That’s the key. The risks are not theoretical. They are here. The urgency is real.

The CISO as the Enabler

The role of the CISO is changing. In the era of agentic AI, it is less about being the gatekeeper and more about being the enabler, the one who provides the safe pathways for AI adoption.

The organizations that succeed will be those that confront shadow AI head-on, establish governance early, and enforce identity-centric controls before the footprint becomes unmanageable.

Shadow IT taught us that ignoring invisible adoption only makes it harder to fix later. Shadow AI is moving even faster. Now is the time to bring it into the light.

Call to Action: 5 Steps to Bring Shadow AI Into the Light

1. Launch an AI Agent Discovery Initiative
   Map every agent across cloud, SaaS, and on-prem. Visibility is the foundation.
2. Form an AI Governance Committee
   Include security, legal, compliance, and business stakeholders to review requests and set policy.
3. Define Guardrails for Experimentation
   Allow low-risk AI deployments, while setting clear thresholds for production.
4. Establish AI Agent Lifecycle Rules
   Require that every agent has a start date, purpose, owner, and deprovisioning criteria.
5. Prepare for Regulatory Scrutiny
   Align today with EU AI Act, ISO 42001, and emerging frameworks. Build your evidence trail before auditors come knocking.

These steps don’t stop innovation. They accelerate it by making AI adoption sustainable, defensible, and trustworthy. Shadow AI becomes structured AI only when CISOs step in with governance. 

Token Security provides a purpose-built solution for securing agentic AI by providing visibility, control and governance. To learn more, schedule a demo of the Token Security Platform.