Understand and govern enterprise AI Agents
AI Agents can act, connect to systems, use tools and operate with increasing levels of autonomy across the enterprise.
Understanding an agent therefore requires more than knowing that it exists. Organizations need visibility into its identity, purpose, ownership, authority, access, delegation, accountability, approval and supporting evidence.
Alterlayer provides public AI Agent discovery tools and enterprise governance capabilities that help organizations move from identifying an agent to understanding how it should operate.
Discovery to governance
AI Agents- 01
Discover
Inspect available public information about an AI Agent, domain or MCP Server.
- 02
Understand
Establish the agent's identity, purpose, capabilities and available technical context.
- 03
Assess
Identify whether the governance information required for the agent is documented.
- 04
Govern
Connect ownership, authority, access, accountability, approval and evidence to enterprise governance.
From AI Agent discovery to enterprise governance
Public technical information can help establish what an AI Agent declares about itself, its provider, protocols, interfaces or capabilities. That information is useful, but it does not establish how the agent is governed inside an organization.
Enterprise governance requires additional context: who owns the agent, why it is being used, what it is authorized to do, what resources it can access, whether it can delegate actions, who remains accountable and what evidence supports those decisions.
Alterlayer separates these two layers while allowing organizations to connect them.
- 01
Discover
Inspect available public information about an AI Agent, domain or MCP Server.
- 02
Understand
Establish the agent's identity, purpose, capabilities and available technical context.
- 03
Assess
Identify whether the governance information required for the agent is documented.
- 04
Govern
Connect ownership, authority, access, accountability, approval and evidence to enterprise governance.
Free public tool
AI Agent Lookup
AI Agent Lookup is Alterlayer's free public tool for inspecting supported publicly available AI Agent information.
The Lookup can inspect supported A2A Agent Card information and search supported MCP Server information from the Official MCP Registry. Available information is presented in a normalized view with its source and provenance visible.
Alterlayer does not create or replace the underlying public registries or protocols and does not turn Lookup searches into permanent public agent profiles.
Open AI Agent LookupEnterprise governance discipline
Know Your Agent
Know Your Agent, or KYA, applies a governance discipline to enterprise AI Agents.
It asks a different question from traditional customer KYC. The objective is not to use an AI Agent to verify a customer. The objective is to help an organization understand and document the AI Agents that act for it.
Alterlayer's Know Your Agent model examines nine governance dimensions: Identity, Ownership, Purpose, Authority, Access, Delegation, Accountability, Approval and Evidence.
Explore Know Your AgentPrivate in-browser assessment
Assess an AI Agent
The Know Your Agent Assessment helps an organization identify whether essential governance information for an AI Agent has been documented.
The Assessment reviews the same nine governance dimensions and identifies documentation gaps that may require attention.
It does not certify an AI Agent, independently verify submitted information or determine regulatory compliance.
Start Agent AssessmentNine dimensions of AI Agent governance
- Identity
- Can the organization identify the AI Agent and distinguish it from other agents?
- Ownership
- Is responsibility for owning or operating the AI Agent documented?
- Purpose
- Is the business purpose for using the AI Agent documented?
- Authority
- Is it documented what the AI Agent is authorized to do on behalf of the organization?
- Access
- Is the AI Agent's access to enterprise resources documented?
- Delegation
- Is the AI Agent's ability to delegate or invoke other resources documented?
- Accountability
- Is responsibility for the AI Agent's actions documented?
- Approval
- Has the AI Agent's use been formally approved?
- Evidence
- Can the organization produce evidence supporting the governance of the AI Agent?
Public identity is not enterprise governance
An Agent Card, MCP Registry entry, endpoint or other public technical metadata can provide useful evidence about an AI Agent.
It cannot by itself establish the organization's internal business owner, approved purpose, permitted authority, enterprise access, delegation rules, accountability, approval conditions or governance evidence.
This distinction is fundamental to Alterlayer's approach: public information can support understanding of an agent, while enterprise governance determines whether and how that agent should operate for the organization.
Govern AI Agents across vendors and systems
AI Agents may come from different vendors, platforms and internal teams. Technical identity and platform controls remain important, but they do not establish how an organization governs an Agent.
Alterlayer provides a vendor-neutral governance layer for documenting who owns an Agent, why it is used, what it is authorized to do, what it can access or delegate, who is accountable, how its use was approved and what evidence supports those decisions.
Assess an AI AgentHow Alterlayer complements Microsoft Agent controls
Microsoft Entra Agent ID and Microsoft Copilot Studio provide important technical identity, authentication, access, permission, lifecycle and platform-native governance controls for AI Agents operating within Microsoft environments.
Alterlayer does not replace Microsoft Entra, Microsoft Copilot Studio or equivalent vendor-native controls. It provides a vendor-neutral organizational governance layer across AI Agents from Microsoft, other vendors and internal teams.
This organizational layer connects available technical information with the business context that must remain understandable across the enterprise: why an Agent is used, who owns the business decision, what authority it has, what it can access or delegate, who remains accountable, who approved its operation and what evidence supports those decisions.
Technical Agent identity establishes who or what an Agent is within a technical environment. Organizational Agent governance establishes why the enterprise uses it, under whose authority it operates and how the resulting decisions are evidenced.
What is AI agent governance?
AI agent governance is the organizational framework for establishing responsibility, authority, oversight and evidence around AI agents operating within the enterprise.
Agents introduce governance questions that go beyond whether an AI capability exists or who owns the underlying technology.
An organization may also need to understand what an agent is authorized to do, on whose behalf it acts, where human approval is required and how that authority can change over time.
AI agent governance provides a structure for managing those questions as agents become part of enterprise operations.
Govern agents according to what they can do
Not every AI agent creates the same governance requirements.
An agent that retrieves information operates differently from an agent that can initiate a workflow, modify a business record or trigger an external action.
The governance question therefore extends beyond the presence of AI.
The enterprise needs to understand the operational role of the agent and the significance of the actions it can perform.
This creates a basis for applying governance proportionately rather than treating every agent as an identical object.
Make ownership explicit
Every enterprise AI agent should exist within an identifiable organizational context.
Ownership establishes who is accountable for that context and who should respond when governance attention is required.
The owner does not necessarily perform every technical or operational task associated with the agent.
Ownership instead provides a clear point of organizational accountability around the agent's purpose, use and governance state.
This becomes particularly important when agents operate across applications, teams or business processes.
Distinguish the owner, operator and principal
AI agents can involve several forms of responsibility.
The owner may be accountable for the agent within the enterprise.
An operator may administer or operate the agent or the environment in which it runs.
The agent may also act on behalf of a person, team or organization that serves as its principal.
These roles should not automatically be treated as interchangeable.
Distinguishing them helps the enterprise understand where responsibility sits when an agent performs work or initiates an action.
Understand the authority delegated to an agent
An agent's technical ability to perform an action does not necessarily mean that the organization has authorized that action.
Governance therefore needs to distinguish capability from authority.
The enterprise may need to understand what authority has been delegated to an agent, the scope of that delegation and the organizational context in which it applies.
This becomes increasingly important as agents move from assisting people to acting within enterprise workflows.
Authority should remain connected to organizational responsibility rather than being inferred solely from technical permissions.
Define where human approval remains required
Delegating work to an AI agent does not require delegating every decision.
Organizations can establish boundaries around actions that require human review or authorization.
Those boundaries may depend on the nature of the action, its business significance and the authority granted to the agent.
Making the human approval boundary explicit helps distinguish autonomous operation from actions that remain subject to organizational decision-making.
The objective is not to prevent agentic operation, but to make responsibility clear where human authority remains necessary.
Connect agents to enterprise visibility and inventory
Agents should not become a separate invisible technology estate.
Enterprise visibility can help identify relevant agents and determine which require further organizational attention.
Once an agent is established as a relevant enterprise AI object, it can be connected to the maintained inventory and its organizational context.
This provides a foundation for ownership, authority and governance without treating every technical observation as a separate governed agent.
Govern changes in agent capabilities and authority
AI agents can change after they are introduced.
Their tools, models, workflows, permissions, business purposes or operational environments may evolve.
Organizational authority can also change independently of technical capability.
A change therefore does not automatically determine a new governance state.
It can instead create a governance question that requires the organization to determine whether ownership, authority, oversight or approval boundaries should be reconsidered.
This preserves the distinction between observing a change and deciding what that change means.
Preserve evidence of authority and governance decisions
Agent governance becomes more durable when the organization can preserve evidence of the decisions surrounding an agent.
Relevant evidence can help establish who was accountable, what authority was granted, what boundaries applied and how those decisions changed over time.
This is particularly important when agents can initiate actions rather than simply generate information.
Evidence connects the current governance state with the organizational decisions that produced it.
It also reduces dependence on informal knowledge when responsibilities, systems or people change.
Support revocation and reassessment
Delegated authority should not be treated as permanent simply because it was previously granted.
Changes in an agent's capabilities, purpose, ownership or operating environment may require its authority to be reconsidered.
The organization may need to confirm, modify or revoke an existing delegation.
Governance should therefore preserve enough context to understand what authority currently applies and whether a material change requires renewed attention.
This makes authority part of the agent lifecycle rather than a one-time configuration decision.
Keep humans accountable as agents become more autonomous
Greater technical autonomy does not eliminate organizational accountability.
Agents can perform increasingly complex work, but enterprises still need identifiable responsibility for the authority under which those agents operate.
Technology can support discovery, information collection, routing and evidence.
The enterprise remains responsible for deciding what an agent is permitted to do and where human intervention or approval is required.
AI agent governance provides the organizational structure for maintaining that connection as agent capabilities evolve.
Make AI agent governance an operating capability
AI agent governance should not depend on reconstructing responsibility each time an agent changes or a new question arises.
The enterprise needs a repeatable way to identify relevant agents, establish ownership, understand delegated authority, maintain appropriate human approval boundaries and preserve evidence.
That operating capability becomes increasingly important as the number and capabilities of enterprise agents grow.
The objective is not to create a separate governance universe for agents.
It is to extend enterprise AI governance to the additional questions created when AI can act.
Make AI Agents governable
AI Agents are becoming part of the enterprise operating environment. As their autonomy and access increase, organizations need a consistent way to understand what agents exist, who is responsible for them and under what conditions they may operate.
Alterlayer connects AI visibility, ownership, governance and evidence so organizations can move from discovering AI Agents to governing them as enterprise assets.
Start with AI Agent Lookup, then understand Know Your Agent and assess the governance information documented for an agent.