Autonomous AI agents are quickly becoming part of everyday work, and some of their most consequential tasks now sit between companies rather than inside them. The more capable AI agents become, the more complex the workloads they’re taking on, and it has become common for them to work across company boundaries to perform tasks like customer support, vendor procurement, or billing reconciliation.
Agents are changing the way businesses interact with their partners and external vendors, and B2B identity management needs to catch up. It was built on the assumption that whoever logs in from a partner organization is a person, usually authenticating through their own company’s single sign-on. But that’s no longer the case, as more and more people at partner organizations hand work off to agents acting on their behalf.
Organizations can no longer rely on just verifying which person is logging in. Instead, they need to determine which partner an AI agent is acting for, which individual within that organization granted it the authority to act on their behalf, and what happens to their access rights when that person’s own access is revoked.
Agents Are Now Part of the Partner Relationship
B2B identity management governs the employees of partner and customer organizations by treating each organization as its own isolated tenant. Within these tenants, users are federated through the partner’s own identity provider, which lets each organization onboard its users when they need access and offboard them when it’s no longer necessary.
AI agents currently arrive in the system using the same business relationships. Virtually every agent is set up by a specific human employee at a specific partner organization, which means they operate within the established B2B identity management framework.
Agents are essentially just a digital extension of the employee that controls them, and so their access should be bound by the same organizational rules and hierarchies.
Why Static Service Accounts Break Down
The first time a business comes across an external agent requesting access to its network, it’ll likely default to the usual procedure of issuing that agent a static API key or standard service account, in the same way they would if a human user requests access.
But the risks of doing this can quickly cascade. The problem is that AI agents multiply fast, leading to credential sprawl as thousands of them are given permission to access partner systems. The more agents pop up, the more API access keys are doled out, and the harder they become to track, especially when they’re spread across dozens of partner organizations.
Another weakness of static accounts is that they rely on hardcoded privileges that don’t provide any context about which organization or human employee the agent is working for. This can create an unacceptable cross-tenant risk. An agent whose access is never revoked could accumulate excessive privileges granting it access to the data of multiple partners.
Such systemic authority goes against the foundational zero-trust security principle of least privilege-based access, creating unnecessary vulnerabilities that sophisticated attackers will try to exploit.
Tie Every Agent to an Organization and a Delegator
To avoid these problems, organizations need a new way to govern access for machine-based entities. Instead of API keys, organizations need to think in terms of delegation. AI agents must inherit the same tenant scope of the businesses they work for, and should never be granted permissions that exceed those of the human user who is orchestrating them and delegating the authority.
The best way to give partner agents access is through delegated, tightly scoped and short-lived credentials. Organizations can keep a tight lid on AI agents using techniques such as OAuth on-behalf-of workflows and token-exchange mechanisms, which ensure they only have temporary access for as long as they need to complete a certain task. Once the job is done, their access will automatically be revoked.
Zanzibar-style relationship-based access control or ReBAC is an authorization model that grants or denies access based on the dynamic connections between users, services and objects instead of static roles and lists. It’s a fine-grained architectural approach that’s perfect for AI agents, allowing complex, multi-layered rules to be expressed and validated. It gives systems a way to verify that “Agent A is working on behalf of User B, who is an employee of Company C, who is authorized to access resource D.”
By building relationship-based authorization into their B2B identity management framework, organizations can seamlessly scale these security checks to ensure every AI agent is tightly bound to the human controlling it.
Offboarding Has to Reach the Agents
B2B identity management can’t stop at granting agents access. It also has to revoke access. Credential sprawl is an unacceptable risk when there are thousands of agents running around inside their systems. Organizations must ensure that access is only available to entities that have a reason to do so. With human users, when an employee leaves a partner organization, that person’s access is revoked at the identity provider level. But if the individual’s AI agents aren’t bound by the same rules, they can be forgotten when their delegators are offboarded.
When a partner revokes the access of an employee, every agent tied to that person must also be locked out. The same applies at the organization level: if the business relationship ends, every agent operating within that partner’s tenant should lose access at the same time. The simplest way to do this is with System for Cross-domain Identity Management (SCIM) deprovisioning that automatically extends offboarding to AI agent credentials, too.
Finally, organizations should ensure their partner’s security administrators have visibility into the autonomous agents acting within their tenant. Delegated administration tools enable partner admins to see, manage and audit these agents in the same way as they can with their human employees. This helps to prevent the accumulation of orphaned “shadow agents” that can retain lingering access to critical systems long after their human users have left the company.
Traceability and Governance
Every agent action should be traceable back through the full delegation chain. That means audit logs need to record not just what the agent did, but the person it acted for and the partner organization that person belongs to.
This kind of traceability also helps organizations demonstrate accountability under Europe’s General Data Protection Regulation (GDPR).
The EU AI Act adds another consideration. Its logging and human-oversight requirements for standalone high-risk AI systems now apply from December 2027. Most agent activity won’t fall into that category, but some autonomous agents may.
Final Thoughts
Extending B2B identity and access management to AI agents starts with an inventory of the agents each partner organization is running. Then replace static API keys with delegated, short-lived credentials. Next, ensure that automated deprovisioning is extended to cover the agents each human identity has authorized to act on their behalf. Finally, make sure that audit trails cover the entire extent of the delegation chain, so admins can trace each agent’s action back to the human that authorized it.
Automation is the new reality, and agents can no longer be bolted onto B2B identity management as an afterthought. Security teams have to treat them as first-class identities, just like human employees, and govern them within the same organization and tenant model.
