Identity and access management for AI agents

AI agents access your data, take actions and delegate tasks, without human intervention at every step. With Memority, extend your identity governance to AI agents: a dedicated identity, a named owner, access rights tailored to each mission and end-to-end traceability.

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What current processes miss

Four blind spots in AI agent governance

Illustration du cycle de vie d'une identité d'agent IA : création, modification des accès et révocation des identifiants

A lifecycle that's hard to manage

Without joiner or leaver processes, an agent's credentials can remain active long after its mission has ended.

Illustration d'un agent IA rattaché à un propriétaire responsable de ses droits d'accès et de ses actions

Ownerless agents

Every agent, or every agent fleet, needs a named owner who is accountable for its access and actions, from deployment to decommissioning.

Illustration du Shadow AI : agents IA utilisant les identifiants de leur créateur, hors de la gouvernance des identités

Shadow AI out of control

SaaS copilots, scripts, MCP servers: some agents run on their creator's credentials, without being identified or governed by IT.

Flux lumineux dans un centre de données, illustrant l'accumulation de droits d'accès non recertifiés par les agents IA

Access rights that drift unchecked

As their missions evolve, AI agents accumulate access rights that are not systematically recertified.

Governance fundamentals

Five questions to assess how well you control your AI agents

1. Which AI agents are active?
You can't govern AI agents until you can identify all of them, including those deployed outside standard IT processes. That means knowing:
- How many AI agents are active across your information system?
- Which ones were deployed by business teams or through SaaS platforms?
- Does each agent have its own identity, separate from its creator's?
The goal: gain full visibility over your AI agents so their identities and access can be brought under your governance.
2. Who is accountable for each AI agent?
Every AI agent must be assigned to a clearly identified owner. That accountability means knowing, at every stage of its lifecycle:
- Who oversees its use?
- Who approves its access rights and any changes to them?
- Who can decide to suspend or deactivate it?
The goal: ensure clear accountability for every AI agent, from creation to deactivation.
3. What rights and permissions does it have?
An AI agent's capabilities depend in particular on its skills, its toolset and the data sources available to it. But having these capabilities doesn't mean it is authorized to use them without restriction. You therefore need to define precisely:
- Which tools and actions is the agent authorized to use or perform?
- Which data sources can it access, and within what limits?
- Are its permissions recertified when its mission or capabilities change?
The goal: ensure every AI agent holds only the permissions its mission requires, even as its capabilities evolve.
4. Can its access be suspended at any time?
An AI agent can carry out many actions autonomously. Staying in control means being able to step in quickly, without necessarily halting all of its activity. That requires knowing:
- Who is authorized to suspend or revoke its access?
- Can access to a specific tool be disabled, or a specific delegation revoked?
- Do revocation decisions take effect immediately, including during an active session?
The goal: be able to suspend or restrict an AI agent's access at any time, in a targeted way, without waiting for its access tokens to expire.
5. Can its actions be audited?
Governing AI agents requires full traceability of their actions and of access decisions. To ensure auditability, you need to be able to determine:
- Who initiated an action, and which agents were involved in carrying it out?
- Which rights were used, and under which authorizations?
- Are the logs and evidence required for audits available and usable?
The goal: reliable traceability to reconstruct AI agent actions, justify access decisions and meet audit requirements.

Deux collaborateurs analysent un écran pour évaluer la visibilité, les droits d'accès et l'auditabilité de leurs agents IA

1. Which AI agents are active?

You can't govern AI agents until you can identify all of them, including those deployed outside standard IT processes. That means knowing:

How many AI agents are active across your information system?

Which ones were deployed by business teams or through SaaS platforms?

Does each agent have its own identity, separate from its creator's?

The goal: gain full visibility over your AI agents so their identities and access can be brought under your governance.

2. Who is accountable for each AI agent?

Every AI agent must be assigned to a clearly identified owner. That accountability means knowing, at every stage of its lifecycle:

Who oversees its use?

Who approves its access rights and any changes to them?

Who can decide to suspend or deactivate it?

The goal: ensure clear accountability for every AI agent, from creation to deactivation.

3. What rights and permissions does it have?

An AI agent's capabilities depend in particular on its skills, its toolset and the data sources available to it. But having these capabilities doesn't mean it is authorized to use them without restriction. You therefore need to define precisely:

Which tools and actions is the agent authorized to use or perform?

Which data sources can it access, and within what limits?

Are its permissions recertified when its mission or capabilities change?

The goal: ensure every AI agent holds only the permissions its mission requires, even as its capabilities evolve.

4. Can its access be suspended at any time?

An AI agent can carry out many actions autonomously. Staying in control means being able to step in quickly, without necessarily halting all of its activity. That requires knowing:

Who is authorized to suspend or revoke its access?

Can access to a specific tool be disabled, or a specific delegation revoked?

Do revocation decisions take effect immediately, including during an active session?

The goal: be able to suspend or restrict an AI agent's access at any time, in a targeted way, without waiting for its access tokens to expire.

5. Can its actions be audited?

Governing AI agents requires full traceability of their actions and of access decisions. To ensure auditability, you need to be able to determine:

Who initiated an action, and which agents were involved in carrying it out?

Which rights were used, and under which authorizations?

Are the logs and evidence required for audits available and usable?

The goal: reliable traceability to reconstruct AI agent actions, justify access decisions and meet audit requirements.

Governance, security and compliance

Our approach to AI agent governance

Visibility over your AI agents
In our approach, discovering an AI agent is only the starting point. The real question is what happens to it next: approved, brought under control or retired. Shadow AI isn't tackled by banning it, but through a deliberate governance decision.
One identity, one owner, one lifecycle
An AI agent exists to fulfill a mission, and a human is accountable for it. For Memority, the mission justifies its access, while accountability defines who makes decisions at every stage. When either one changes, the agent's future must be decided.
Controlled delegation
Delegating a task to an agent should never mean lending it your identity. For Memority, delegation is built on least privilege: rights limited to the mission and capped by the user's own.
Right-sized, recertified access
AI agents evolve faster than access review campaigns. For Memority, recertification should follow the changes that genuinely alter an agent's scope: risk, not routine, sets the pace.
Access control and enforcement
A governance decision that doesn't change access is just a statement of intent. For Memority, what is decided at the identity level must be reflected in what the agent can actually do. That consistency is what puts you back in control.
Traceability, compliance and a European foundation
Governing an AI agent also means being able to understand and justify its actions. For Memority, traceability goes beyond collecting logs: it must link actions to identities, accountability and authorizations, as part of an approach built on control and European sovereignty.

Ville au coucher du soleil traversée de flux lumineux, symbole des accès et des échanges de données entre agents IA

Let's talk about governing your AI agents

Are your teams already deploying AI agents? Share your use cases with our IAM experts. We'll present our vision for AI agent management and discuss your governance priorities.

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FAQ

Frequently asked questions about AI agent access management

All questions

Why does an AI agent need its own identity?
An AI agent can access data, use tools and act on behalf of a user or another agent. Giving it a distinct identity makes it possible to define its own permissions, trace its actions and establish accountability at every step.
Who is accountable for the actions an AI agent performs?
Even when it acts autonomously, an AI agent must remain under the responsibility of a clearly identified person. Memority lets you formalize this accountability and trace the delegations, access and actions carried out throughout the agent's lifecycle.
How is an AI agent different from other non-human identities?
Like a service account, an AI agent accesses resources without direct human intervention. What sets it apart is its ability to interpret a goal, select tools and chain actions that aren't always defined in advance. Its governance must therefore take into account its mission, its delegations and how its capabilities evolve, not just its access.
What is an AI agent identity (agentic identity)?
An AI agent identity, or agentic identity, is a digital identity distinct from that of its creator or of the user it acts on behalf of. It makes it possible to identify the agent, assign it an owner, define its permissions and manage its lifecycle.
Does an AI agent inherit the rights of the user who launched it?
Not necessarily. When an AI agent acts on behalf of a user, its permissions should be limited to what its mission requires, without giving it access to all of that user's resources. Memority lets you govern this delegation and control the rights actually granted.
Do AI agents require a new IAM framework?
No. AI agents can be brought into your existing IAM governance. Like any other identity, they must be identified, authenticated, authorized and monitored throughout their lifecycle. Memority extends these principles to the specific characteristics of AI agents, including their autonomy and delegation capabilities, within a unified platform.
Why a decision engine rather than a gateway that decides on its own?
A gateway controls access to tools, but doesn't necessarily have all the identity governance context. By centralizing authorization decisions in a dedicated engine based on the OpenID AuthZEN standard, Memority enforces consistent access policies that take into account agent identities, their rights and their lifecycle.

Discover our other use cases

Employees

Simplify identity management for your employees and contractors, combining security, productivity and compliance.

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Partners

Simplify partner identity management across your ecosystem with Memority's IAM solution.

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Customers

Simplify customer identity management with a comprehensive CIAM solution designed for a unified and scalable approach.

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Identity and access management for AI agents

They trust us

Four blind spots in AI agent governance

A lifecycle that's hard to manage

Ownerless agents

Shadow AI out of control

Access rights that drift unchecked

Five questions to assess how well you control your AI agents

1. Which AI agents are active?

2. Who is accountable for each AI agent?

3. What rights and permissions does it have?

4. Can its access be suspended at any time?

5. Can its actions be audited?

Our approach to AI agent governance

Visibility over your AI agents

One identity, one owner, one lifecycle

Controlled delegation

Right-sized, recertified access

Access control and enforcement

Traceability, compliance and a European foundation

Let's talk about governing your AI agents

Frequently asked questions about AI agent access management

Why does an AI agent need its own identity?

Who is accountable for the actions an AI agent performs?

How is an AI agent different from other non-human identities?

What is an AI agent identity (agentic identity)?

Does an AI agent inherit the rights of the user who launched it?

Do AI agents require a new IAM framework?

Why a decision engine rather than a gateway that decides on its own?

Employees

Partners

Customers