Agentic Identity Governance: Staying in Control when Agents Multiply

You want to let teams build and use agents without creating a parallel identity estate you cannot explain, audit, or shut down. You want autonomy with boundaries, and speed with accountability.

Why Governance Fails in Predictable Ways

Governance for AI agents fails in predictable ways. Not because people do not care, but because the old playbooks assume either a human user or a classic application. Agents sit in the middle: they can act with user-like impact, with application-like persistence, and they can do it without waiting for anyone.

That “middle” is what breaks muscle memory. Human users come with HR ownership, joiner mover leaver processes, and an org chart. Classic apps tend to be scoped to a system and a team. Agents can behave like a digital coworker one minute and like a background service the next, while still being able to call APIs, trigger workflows, and touch sensitive data. Microsoft’s own Entra Agent ID guidance draws a clear line between human identities and agent identities, precisely because agents need a different governance approach than standard user accounts.

Agent Sprawl is What it Looks Like in Production

Microsoft describes the resulting mess as agent sprawl. It shows up as shadow AI created outside formal oversight, rapid proliferation across teams, weak lifecycle practices, permission creep, and lost accountability. The consequence is simple: you cannot prove control to yourself, to audit, or to incident response.

The phrase matters because it names the real pattern: agents multiply faster than the organization’s ability to track ownership and intent. Permission creep is common because broad access is the fastest way to get an early win, and then those permissions rarely get revisited. Lost accountability follows because the creator is not always the operator, and the operator is not always the business owner. Microsoft calls out both permission creep and lost accountability as core risks when agents proliferate.

What “workable governance” Actually Requires

A workable governance model needs two things: an identity model that matches the problem, and an operating model that people can actually run.

If you only do the identity model, you get a nice architecture diagram and the same operational drift as before. If you only do operating model, you end up with policy documents nobody can enforce. Governance that survives scale is the combination of a standard identity pattern plus a repeatable way of owning, reviewing, and retiring agent identities.

The Identity Model Microsoft is Building for Agents

Entra Agent ID is the identity model Microsoft is putting behind agent governance in the Entra ecosystem. It introduces agent identity blueprints as templates, agent identities as special service principals created from those templates, and optional agent users for scenarios where a system requires a user object. It also introduces an agent registry concept for discovery and metadata.

This is not a cosmetic change. In the Entra Agent ID model, the blueprint is the control surface and the agent identity is the instance created from that control surface. Microsoft describes an agent identity as a special service principal created by the blueprint and authorized to be impersonated by it, and it notes that agent identities do not hold credentials on their own. That design is what makes standardization and inheritance possible at scale, instead of every agent becoming its own snowflake identity.

The registry concept matters for a more basic reason: you cannot govern what you cannot find. A discovery layer that carries metadata is what turns governance from guessing into decisions.

The Operating Model Starts With Relationships, not Settings

The operating model starts with administrative relationships. Microsoft separates owners, sponsors, and managers. Owners are technical administrators. Sponsors provide business accountability and make lifecycle decisions without needing technical configuration access. Managers relate to agent users and organizational hierarchy. Most importantly, a sponsor is required when creating an agent identity or an agent blueprint, with blueprint principals exempt during creation. That requirement is a governance lever. Use it.

This is where many organizations finally get a chance to fix the orphan problem by design. “Owner” often becomes “the person who created it,” which is a weak form of accountability when teams change. “Sponsor” is intended to be durable accountability: the human or group that can answer why the agent exists and whether it should continue to exist. Microsoft’s administrative relationships documentation is explicit about the sponsor requirement and the exemption for blueprint principals during creation.

Sponsors Are The Control Point

From a governance perspective, sponsors are your control point. A sponsor answers three questions in plain language: what is this agent for, what data is it meant to touch, and what would “done” look like so we can retire it. Owners implement the controls. Sponsors justify the existence.

This split is practical. Owners can handle configuration and access patterns. Sponsors make the decision that matters in governance: does the business still accept the risk and cost of this agent running. If your sponsor cannot explain the purpose in one sentence, the agent is not ready for production.

Agent Users Are Powerful, And Governance-heavy For a Reason

Agent users deserve special attention because they look and feel like a person in your tenant. Microsoft positions agent users for long term “digital employee” scenarios, including mailboxes and chat access, inclusion in HR systems, and collaboration workflows. They receive tokens with idtyp=user and can be assigned licenses, which is often necessary for Microsoft 365 resources. That makes them powerful, and that makes them governance heavy.

The risk is not theoretical. The moment an agent has user-like presence, it becomes eligible for user-bound capabilities and collaboration surfaces. Microsoft’s Entra Agent ID model distinguishes agents from human identities, but also acknowledges that some scenarios need user representation because the workload expects a user object with the related M365 experiences and data. That is why agent users exist, and why they should be treated as the exception, not the default.

Treat Agent Users as an Exception, by Policy

A strong policy stance is that agent users are exceptional. Most agents should not need them. When an agent needs user-only capabilities, you should treat that as a governance event with stricter approval, tighter scope, and more frequent review.

This is where control is won or lost. If every team reaches for agent users because it is convenient, you will quickly recreate the mess you already know from unmanaged user accounts, just with automation attached. If you make agent users rare, you keep most agents in a governed, app-like posture where scope and boundaries are easier to enforce.

Lifecycle Governance is The Other Half

Lifecycle governance is the other half. Microsoft’s security guidance for AI agents emphasizes the need to identify deployed agents, document purpose and permissions, and maintain audit trails of actions and data access. When you connect that to agent sprawl, the control set becomes obvious: registration at creation, minimum metadata, expiry, access reviews, and logging that supports investigation.

This is the practical bridge between “we have rules” and “we can prove control.” Identification and documentation give you discoverability. Audit trails give you evidence. Reviews and expiry give you renewal decisions instead of permanent drift. Microsoft’s guidance on security for AI agents in Entra Agent ID calls out the need to manage these risks because sprawl and overprivilege are the default failure mode when organizations scale agents.

Why the Cloud Adoption Framework Matters Here

This is also where the Cloud Adoption Framework helps. It frames governance and security across the organization as layered. Data governance and compliance is not optional. Observability is not a later improvement. Security controls and safe development practices must exist before scale. The moment agents become common, you need organization-wide policy, not team-level preferences.

Microsoft’s AI agent adoption guidance puts governance and security ahead of build and operate for a reason. If teams scale agents before the organization has shared guardrails, you get inconsistent patterns and inconsistent risk. That is expensive to unwind later.

Governance is a Contract

Governance should feel like a contract, not a checklist. Each agent gets a sponsor, a scope, and a lifespan. Each agent has a place in a registry. Each agent has boundaries enforced by identity and policy. When the agent misbehaves, you know who can decide to suspend it and who can fix it.

That is what “governable at scale” looks like.

It is not perfect control. It is operational control. The kind you can run on a Tuesday, when nobody has time for a workshop and the agent still needs to behave.