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HIPAA Compliance Checklist for 2025
AI agents are moving beyond experiments and into everyday enterprise work. They can pull data, use business applications, and take actions with limited human input. For CIOs and IT teams, that raises a simple question: Do you know which agents are running, who owns them, and what they can access?
Gartner expects an average Fortune 500 company to have more than 150,000 AI agents by 2028, compared with fewer than 15 in 2025. Yet only 13% of organizations believe they have the right AI agent governance in place.
At that scale, finding agents is only the start. Teams also need visibility into their owners, credentials, and permissions. AI agent discovery tools can help. A non-human identity management tool can help govern the identities and access behind them.
In this blog, you’ll learn which AI agent discovery tools stand out in 2026, what to look for, and how they connect with NHI management.
“Organizations need to find a balance where they can govern agents and manage sprawl, but also safely empower employees to innovate with these tools.”
- Max Goss, Senior Director Analyst, Gartner
What is an AI Agent Discovery Tool?
An AI agent discovery tool helps teams find and track AI agents across SaaS, cloud, endpoints, and internal systems. It shows who owns an agent, what it can access, and which credentials or NHIs it uses.
In simple terms, it answers three questions: What agents exist? Who owns them? What can they access?
This visibility helps teams spot shadow agents, excessive permissions, and unmanaged identities before they become bigger security or governance issues. A non-human identity management tool can then help connect those findings to ownership and access controls.
Best AI Agent Discovery Tools in 2026
AI agent discovery tools do not all work the same way. Some find agents through SaaS APIs, while others use browser, endpoint, cloud, or identity signals to uncover activity that traditional inventories can miss.
NHI-focused platforms go a step further by linking agents to credentials, permissions, owners, and resources.
We evaluated these tools on discovery coverage, shadow AI visibility, identity context, effective permissions, ownership, MCP connectivity, risk, lifecycle controls, and remediation. The list focuses on enterprise fit rather than treating every platform as a like-for-like solution.
1. CloudEagle.ai: Best for NHI Discovery and Governance
CloudEagle.ai treats AI agents as part of the wider non-human identity (NHI) problem. An agent may rely on an API key, OAuth token, service account, or another machine identity to access business applications.
Finding the agent without understanding those identities leaves a major part of the risk surface unseen.
Key capabilities:
- Discovers and inventories NHIs across SaaS environments
- Connects identities with owners, applications, permissions, and activity
- Flags inactive, ownerless, and overprivileged identities
- Supports remediation such as access revocation and credential rotation
Why it matters: Teams can move from simply finding an agent to understanding and governing the identity it uses. CloudEagle says its platform governs AI agents and other NHIs across 500+ SaaS applications.
Best for: Organizations that want AI agent discovery tied to a non-human identity management tool and SaaS governance strategy.
Customer proof: In one CloudEagle.ai deployment, NHI visibility increased from 40% to 95%, with 480 unmanaged NHIs remediated and 220+ overprivileged identities optimized.
Take control of AI agents and NHIs
2. Cisco + Astrix Security: Best for Agent and NHI Security
Astrix brings AI agent and NHI security into Cisco's broader security stack. Its technology maps agents to MCP servers, NHIs, secrets, permissions, owners, and resources, giving teams a clearer view of an agent's access paths.
Key capabilities:
- Discovers AI agents, MCP servers, NHIs, and secrets
- Maps agent-to-resource relationships
- Identifies excessive or unused access
- Supports identity and access controls
Why it matters: The value is in connecting an agent to the identities and resources it can reach, rather than treating agent discovery as a simple inventory task.
Best for: Organizations looking to extend AI-agent and NHI security through the Cisco security ecosystem.
3. Nudge Security: Best for Shadow AI Agent Discovery
Nudge focuses on a problem traditional discovery methods can miss: agents employees create or use without IT approval. It combines platform API integrations with browser-based discovery to expand visibility beyond connected applications.
Key capabilities:
- Discovers agents across supported SaaS and AI platforms
- Uses browser-based discovery for shadow agents
- Maps agents to their creators and permissions
- Identifies risky or unmanaged agent connections
Why it matters: API integrations can provide rich configuration data, but they cannot cover every platform. Browser-level discovery helps close that visibility gap.
Best for: IT and security teams where shadow AI is the immediate concern.
4. Microsoft Defender: Best for Microsoft-Centric Enterprises
Microsoft Defender brings AI-agent inventory into the existing Microsoft security stack. It can provide visibility into agents across Microsoft platforms, supported third-party environments, and endpoints.
Key capabilities:
- Centralized AI agent inventory
- Identity, endpoint, tool, and access context
- Risk indicators and security recommendations
- AgentsInfo data through Advanced Hunting
Why it matters: Teams can correlate agent activity with existing identity, endpoint, and threat telemetry rather than maintaining a separate security inventory.
Best for: Enterprises already invested in Microsoft Defender, Entra, Microsoft 365, and endpoint security.
5. Okta: Best for Agent Identity Governance
Okta approaches AI agents as identities that need authentication, authorization, ownership, and lifecycle controls. Its 2026 capabilities include an agent registry, agent discovery, and policies for agent-to-agent connections.
Key capabilities:
- Agent registration and inventory
- Owner and purpose mapping
- Least-privilege access
- Agent-to-agent authorization policies
- Lifecycle and deprovisioning controls
Why it matters: Organizations can bring AI agents into an existing IAM model instead of creating a separate identity silo.
Best for: Enterprises looking to extend an established IAM architecture to AI agents.
6. CrowdStrike: Best for Endpoint and Runtime Visibility
CrowdStrike approaches AI-agent discovery from the endpoint and security operations layer. Its 2026 capabilities extend visibility across endpoints, SaaS, browsers, and cloud environments.
Key capabilities:
- Detects local AI agents and AI runtimes
- Discovers MCP servers and AI components
- Adds device, user, and privilege context
- Correlates agent activity with security telemetry
Why it matters: Local agents can interact with files, applications, credentials, and other resources on employee devices. Endpoint telemetry can expose activity that SaaS-only discovery may miss.
Best for: Security teams already using CrowdStrike for endpoint and threat visibility.
7. SailPoint: Best for Enterprise Identity Governance
SailPoint brings AI agents into the same identity governance framework used for human and machine identities. Its Agentic Fabric connects agents with owners, applications, data, and other identities.
Key capabilities:
- AI agent and NHI discovery
- Ownership and relationship mapping
- Lifecycle governance
- Least-privilege controls
- Shadow AI visibility
Why it matters: An agent's risk depends heavily on the identities and access it inherits. Mapping those relationships gives identity teams a clearer basis for access decisions.
Best for: Large enterprises with established identity governance programs. SailPoint also completed its Entro Security acquisition in June 2026, expanding its NHI and credential capabilities.
8. Oasis Security: Best for NHI and AI Security
Oasis approaches AI-agent security through the broader NHI attack surface. Its platform discovers AI agents, unauthorized tools, and other machine identities across SaaS, cloud, and endpoint environments.
Key capabilities:
- Continuous AI-agent and NHI discovery
- Ownership and dependency context
- Least-privilege enforcement
- Credential and lifecycle controls
Why it matters: An agent's existence tells you very little about its actual risk. Connecting the agent to its identity, dependencies, and permissions gives security teams the context needed to tighten access.
Best for: Organizations building an NHI security program that includes AI agents.
9. Reco: Best for AI Agent Discovery Across SaaS
Reco focuses on finding AI agents across the SaaS environment and mapping them to owners, identities, permissions, connections, and risk. Its discovery combines API, identity provider, CASB, browser, and network signals.
Key capabilities:
- Builds an inventory of AI agents across SaaS
- Maps agents to owners, identities, permissions, and connections
- Flags overpermissioned and orphaned agent identities
- Provides continuous posture monitoring and remediation
Why it matters: Reco connects agent discovery with the access and identity context needed to assess risk, rather than treating inventory as the end goal.
Best for: Enterprises looking for broad SaaS-based AI agent discovery with identity governance and threat detection. Reco currently supports 260 apps and says its platform maps agents across API, IDP, CASB, browser, and network sources.
10. Aembit: Best for Agent-to-Resource Access
Aembit takes a runtime-focused approach. Rather than concentrating mainly on inventory, it controls whether an agent should access a resource at a specific point in time.
Key capabilities:
- Agent and workload identity
- Runtime access policies
- MCP access controls
- Short-lived credentials and token exchange
- Audit trails for agent activity
Why it matters: Agents do not need permanent credentials embedded in their workflows. Access can be evaluated against policy, granted for a specific task, and allowed to expire afterward.
Best for: Enterprises that need granular control over agent-to-tool and agent-to-resource access.
AI Agent Discovery vs. Non-Human Identity Management
Finding an AI agent is just the first step. AI agent discovery tools can show you where agents exist and how they connect to your environment, but that visibility does not always explain the identities and credentials behind them.
This is where non-human identity management comes in.
A non-human identity management tool connects the two. Say an AI agent has an OAuth token with access to customer data. Discovery tells you the agent exists.
NHI management helps answer the next questions: Who owns the token? What can it access? When was it last used? Does the agent still need that access?
For CIOs, that is the real value. It turns agent discovery into something IT teams can act on, rather than another inventory sitting in a dashboard.
How to Choose the Right AI Agent Discovery Tool
A long agent list is not very useful on its own. What matters is whether the AI tool helps you understand the access behind each agent and act on it.
Look for:
- Broad discovery: Can it find agents across SaaS, cloud, endpoints, and shadow environments?
- Identity mapping: Can the non-human identity management tool show the API key, OAuth app, service account, cloud role, or NHI behind an agent?
- Access detail: Can you see its actual permissions, scopes, tools, and data access?
- Ownership: Can it flag agents with no clear owner or outdated access?
- MCP visibility: Can it show agent-to-MCP connections and exposed resources?
- Remediation: Can teams revoke access, change permissions, or rotate credentials?
- Integrations: Does it work with the IAM, IGA, SIEM, and cloud tools you already use?
The real test is simple: Can the tool tell you what an agent can access, why it has that access, and when it should be removed?
Conclusion
AI agents can speed up work, but each new agent can also introduce another identity, credential, and access path to manage. Finding those agents is only the first step.
A useful AI agent discovery tool should help teams see who owns an agent, what identity it uses, what it can access, and whether it still needs that access.
As more agents enter the workplace, bringing discovery together with non-human identity management can make it easier to keep machine access visible, controlled, and up to date.
FAQs
1. How do you discover shadow AI agents?
A. Shadow agents can be found by checking SaaS admin consoles, OAuth grants, browser and endpoint activity, cloud environments, and AI platform usage. The goal is to identify agents that were created or deployed without going through formal IT controls.
2. How do you discover AI agents in an organization?
A. AI agent discovery tools can help organizations find agents through SaaS and cloud APIs, identity systems, browser activity, endpoint telemetry, and infrastructure logs. Using several discovery methods helps uncover both approved and shadow agents instead of relying on a single inventory source.
3. Why do AI agents need non-human identities?
A. A non-human identity management tool can help teams assign ownership, limit permissions, trace activity, and revoke access when an agent or credential is no longer needed. AI agents need an identity to authenticate with applications, APIs, databases, and other tools. Using a distinct NHI makes it easier to trace agent activity, limit permissions, assign ownership, and revoke access when the agent or its credentials are no longer needed.
4. What information should an AI agent discovery tool provide?
A. The tool should not only be able to display the name of the AI agent. More details need to be revealed, including owner, identity, credentials, applications used, permissions, MCP servers, and activity history. Furthermore, the tool needs to identify shadow agents.
5. Can AI agent discovery tools find shadow agents?
A. Yes, but it is dependent on the way that the tool discovers the agent. Shadow agents could be running on the endpoint, connecting via SaaS applications, using APIs, or communicating externally. Tools that combine endpoint, browser, SaaS, identity, network, and cloud signals are more effective.
Turn AI Agent Sprawl Into Controlled Access
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