The CISO Checklist for the New AI Agent Reality

AI agents are now acting across SaaS, cloud, and endpoint environments with identities and permissions that traditional controls cannot fully govern. Most enterprises already have more agents in production than they realize, many created without security review.

Across the industry, the research aligns. Gartner, Forrester, NIST, MITRE, OWASP, McKinsey, and the EU AI Office all identify autonomous agent behavior as a new enterprise attack surface that requires visibility, continuous oversight, and real-time controls.

The risk is immediate. Agents today are making decisions, accessing sensitive systems, and triggering high-impact workflows without human validation. Security teams need a clear way to discover agents, govern their access, and enforce safe behavior as adoption accelerates.

This checklist gives CISOs a focused framework to regain control.

1. Map every agent in your enterprise

CISOs need full visibility first. Agent sprawl is now a confirmed industry-wide problem.

• Inventory all agents, their purpose, identity inheritance, and data access paths.
• Include both sanctioned and Shadow AI discovered organically across teams.
• Evaluate each agent’s owner, environment, and integration surfaces.

Industry alignment: Gartner and McKinsey call out agent proliferation as one of the fastest-growing AI risks.

For more depth: Analysis of a rogue coding agent that reveals how hidden agents propagate across cloud and endpoint environments.

2. Accept that you will run many agent platforms

The agent ecosystem will continue to expand across SaaS-native, cloud-built, and endpoint-based tools.

• Build governance around agents, not platforms.
• Standardize policies across OpenAI, Microsoft, AWS, Salesforce, ServiceNow, and home-grown agents.

Industry alignment: Forrester stresses the need for platform-independent guardrails.

For more depth: How multi-platform agent environments already operate in production.

3. Assume rapid sprawl

Agents scale faster than traditional applications. A prototype becomes a business workflow in days.

• Treat every agent as production-impacting unless proven otherwise.
• Apply controls early to avoid retroactive governance.

Industry alignment: NIST highlights emergent, unpredictable behavior without continuous oversight.

For more depth: Threat landscape data showing rapid growth in agent and automation volume in enterprise environments.

4. Track every integration surface

Agents operate through connectors, APIs, MCP servers, identity providers, and databases.

• Map execution paths, tool access, and cross-system dependencies.
• Monitor new integration points continuously.

Industry alignment: MITRE ATLAS warns that these execution paths are prime attack vectors for adversaries.

For more depth: How MCP expands agent integration paths and creates new operational and security surfaces.MCP Report: MCP Deep Dive:

5. Focus on the new threat class

Traditional security focuses on prompts or model safety, but agent risks emerge at the action layer.

• Prepare for prompt manipulation, goal hijacking, tool misuse, and unsafe reasoning.
• Validate agent behavior, not just model output.

Industry alignment: OWASP identifies agent behavior and tool invocation as key risk categories.

For more depth: Agent-centric threats such as context poisoning, tool misuse, and agent-driven exfiltration.https://zenity.io/blog/research/the-owasp-top-10-for-agentic-applications

6. Enforce runtime guardrails

Static controls cannot protect agents that make decisions and take actions dynamically.

• Apply real-time policy enforcement on every attempted action.
• Inspect intent and execution before impact.
• Block unsafe behavior consistently across platforms.

Industry alignment: Gartner highlights real-time enforcement as critical for controlling autonomous systems.

For more depth: How unsafe agent actions are intercepted and blocked at runtime as they execute.

7. Anchor every action in identity

Agents inherit permissions from users, creators, and service accounts.

• Explicitly map what the agent may do and who it acts for.
• Prevent privilege escalation through identity inheritance.
• Require traceability for all agent-initiated actions.

Industry alignment: NIST stresses strong identity boundaries for autonomous decision systems.

For more depth: How agent actions are traced to creators, owners, permissions, and identity-based access paths.

8. Centralize visibility and control

Every platform has its own policies, logs, and guardrails, creating fragmentation.

• Establish a unified control plane for governance, policy enforcement, and monitoring.
• Ensure cross-platform consistency.

Industry alignment: Forrester notes the lack of unified governance tools as a major gap in AI security.

For more depth: How unified oversight of agent behavior reduces fragmentation and risk across environments.

9. Build a platform independent governance layer

Agent governance must outlast individual vendor ecosystems.

• Use a control layer that evaluates identity, intent, and behavior.
• Apply consistent rules across SaaS, cloud, and endpoint agents.

Forrester’s AEGIS framework states that security teams need guardrails that span the entire agentic architecture. They also warn that “few, if any, security controls or control planes exist for agentic AI.” The answer is a single control layer that supervises identity, actions, and behavior across every agent on every surface.

For more depth: Cross-environment governance across Microsoft, Google, AWS, OpenAI, Salesforce, ServiceNow, and others.

10. Prepare for volatility

Agent platforms change quickly and unpredictably.

• Expect rapid evolution of tools, APIs, memory systems, and prompt frameworks.
• Implement governance that remains stable even as platforms shift.

Industry alignment: Gartner warns that early agent platforms have short and unpredictable life cycles.

For more depth: How fast agent ecosystems are evolving and why security must be continuous, not point-in-time.

AI agents are moving into the center of enterprise work. They now influence revenue operations, customer interactions, data flows, and internal decisions. This shift can drive remarkable leverage, but only if CISOs stay ahead of the behavior that makes agents useful and dangerous at the same time. Leaders who build governance around identity, intent, and real time action will guide their organizations with confidence. The ones who wait will find the risks scaling faster than their teams. The agent layer is where control returns. The sooner it is built, the stronger the position becomes.