For years, identity strategy was primarily about people.
Organizations needed to know who an employee was, how that employee authenticated, which applications they could access, what privileges they had, and how access changed when they joined, moved within, or left the company.
Cloud computing expanded the challenge. Applications, service accounts, workloads, APIs, and automated processes also needed identities and permissions.
AI agents are adding another layer.
As Microsoft expands agentic capabilities across Microsoft 365, Copilot Studio, Azure, and the broader Microsoft ecosystem, organizations are entering an environment where humans, applications, and AI agents may all need to access the same business systems and information.
That makes identity one of the most important control points in the next phase of enterprise AI.
The identity question is no longer simply, "Who is this user?"
It is becoming, "What is requesting access, on whose behalf, for what purpose, with which permissions, from which device or workload, and under what conditions?"
As Microsoft heads toward Ignite 2026, organizations should expect identity to remain central to the AI and security conversation because nearly every new capability depends on trustworthy access.
AI Agents Need Identities of Their Own
An AI agent may be able to retrieve information, call an API, interact with Microsoft Graph, connect to SharePoint, update a business application, or execute a workflow. To do those things securely, the organization needs to know which agent is acting and what the agent is allowed to do.
Microsoft Entra Agent ID is designed specifically for that challenge. Microsoft now provides agent identities as a distinct identity construct for AI agents rather than forcing organizations to treat every agent like a traditional application or human user.
That distinction matters.
Humans authenticate using methods such as passwords, passkeys, multifactor authentication, and authenticator applications. Traditional applications use application identities and credentials. Agents may act autonomously, assist a specific user, invoke tools, or take actions across systems.
Those behaviors create different identity requirements.
A mature identity strategy needs to account for each type without blurring the boundaries among them.
Every Agent Should Be Identifiable
The first principle of agent identity is straightforward: every agent performing meaningful work should be identifiable.
If an agent changes a record, accesses a site, triggers a workflow, or calls an API, security and IT teams should be able to determine which agent performed the action.
That is essential for troubleshooting, monitoring, auditing, incident response, and governance.
Microsoft's agent identity model includes concepts such as agent identities, reusable identity blueprints, and sponsors. Those elements provide a framework for understanding not only that an agent exists, but also what kind of agent it is and who is accountable for it.
This is an important shift. AI agents should not become anonymous automation operating behind shared credentials or loosely managed service accounts.
Identity provides accountability.
Least Privilege Has to Extend Beyond Employees
Most organizations already understand the principle of least privilege for human users, even if implementing it consistently remains difficult.
Employees should receive the access required for their role and no more. Administrative privileges should be limited. Sensitive access should be reviewed. High-risk actions may require stronger authentication or additional approval.
The same philosophy needs to extend to agents.
An agent that supports customer service should not automatically have broad access to finance data. An agent that schedules meetings should not need privileged directory roles. An agent that summarizes project information may need read access but not the ability to modify records.
The challenge is that agent permissions can become complicated quickly. An agent may operate independently in some situations and on behalf of a user in others. It may connect to multiple systems, call tools, and use data from several sources to complete a task.
That is why permissions need to be designed intentionally rather than added incrementally until the agent works.
Access should match the business purpose of the agent.
Conditional Access Is Part of a Larger Access Decision
Microsoft has spent years moving customers toward Zero Trust principles, where access is evaluated continuously rather than assumed because a user is inside a corporate network.
That approach becomes even more important as identities diversify.
For human users, access decisions can consider factors such as authentication strength, user risk, device compliance, location, application sensitivity, and sign-in behavior. For agents and applications, organizations also need policies that reflect workload identity, permissions, authentication methods, resource sensitivity, and expected behavior.
The objective is a consistent access model across the environment.
Identity should help answer whether a request should be allowed, not merely whether the requesting entity exists.
Device Posture Still Matters in an Agentic Environment
The emergence of AI agents does not make endpoint management less important. In many cases, it makes the relationship between identity and device posture more important.
Employees will continue interacting with Copilot, agents, Microsoft 365, and business applications from laptops, mobile devices, browsers, and managed endpoints. The user's identity may be secure, but access decisions can still depend on whether the device is compliant, encrypted, patched, properly configured, and managed by the organization.
A Zero Trust strategy connects identity with endpoint state.
If organizations are expanding AI access while leaving unmanaged devices, inconsistent Intune enrollment, outdated compliance policies, or weak Conditional Access rules in place, they may be strengthening one layer while leaving another exposed.
That is why identity modernization and endpoint management should be planned together.
Human Identity Lifecycle Problems Do Not Disappear
AI introduces new identity challenges, but organizations still have to solve the old ones.
Dormant accounts, excessive privileges, incomplete offboarding, guest users, shared accounts, stale group memberships, inconsistent multifactor authentication, and poorly controlled administrator roles remain serious issues.
Adding agent identities to an environment with weak human identity governance does not simplify the problem. It increases the number of identities that need to be understood and controlled.
Organizations should continue strengthening joiner, mover, and leaver processes, access reviews, privileged identity management, guest governance, authentication policies, and role design while expanding their approach to non-human identities.
The stronger the core identity program is today, the easier it will be to incorporate agents tomorrow.
Applications and Workloads Need Visibility Too
AI agents are not arriving in an empty environment. Most organizations already have a large population of applications, service principals, integrations, APIs, automation accounts, and cloud workloads.
Many of these non-human identities have accumulated privileges over time. Some use long-lived credentials. Others were created for projects that no longer exist. Some have owners who have left the organization.
Agent identity governance should therefore be part of a broader non-human identity strategy.
Organizations need visibility into applications, workloads, service principals, agents, credentials, permissions, owners, and usage. They should be able to identify dormant identities, excessive privileges, risky credentials, and unknown dependencies.
The objective is not simply to add a new category called "AI agents." It is to create an identity program capable of managing a much more complex mix of actors.
Ownership and Sponsorship Become Security Controls
One of the useful ideas in Microsoft's agent identity approach is the concept of accountability.
An agent can have a sponsor associated with it, helping organizations connect an AI identity to a responsible human or group.
That principle should extend beyond the technical implementation.
Every agent should have someone who can answer why it exists, what it is supposed to do, what data it needs, which systems it can access, and whether it is still required.
The same should be true for applications and other non-human identities.
Ownership becomes a security control because unidentified and orphaned identities are difficult to review, difficult to retire, and easy to overlook during security events.
Auditability Will Become More Important
When a human employee performs an action, organizations often have multiple signals available to understand what happened. They can review sign-in history, application logs, endpoint data, email activity, and other telemetry.
Agents need similar accountability.
Organizations should be able to trace authentication, access, tool use, permissions, and actions back to a specific agent identity. They should know whether the agent was acting autonomously or on behalf of a user and whether the action was consistent with its approved purpose.
That visibility will become increasingly important as agents move from answering questions to executing business processes.
The more authority an agent receives, the more important its identity and audit trail become.
Identity Is Becoming the Policy Layer for AI
The larger lesson is that identity is becoming one of the primary ways organizations will govern AI behavior.
AI governance discussions often focus on policies, acceptable use, data classification, and model risk. All of those matter. But when an agent actually attempts to access a resource or take an action, identity and authorization determine whether that action is allowed.
That makes identity a practical enforcement point for AI governance.
Organizations can define what an agent is, who owns it, which resources it can access, what permissions it has, and under what conditions those permissions can be used.
This is where high-level AI policy becomes operational control.
What L3 Is Watching Heading Into Microsoft Ignite
Microsoft's AI strategy is increasingly connected to identity. Copilot experiences rely on user permissions. Work IQ is permission-aware. Agents need identities. Microsoft Entra is expanding to secure both human and non-human access. Endpoint posture continues to influence Zero Trust decisions.
Those pieces are converging.
As Microsoft continues advancing its AI and security roadmap around Ignite, organizations should view identity modernization as foundational preparation rather than a separate security project.
The work can begin now: strengthen authentication, review Conditional Access, improve privileged access, clean up stale identities, understand application permissions, establish ownership for non-human identities, improve endpoint compliance, and define how new agent identities will be governed.
L3 Networks helps organizations connect those controls across Microsoft 365, Entra, endpoints, security, and the broader Microsoft environment. The goal is to create an access model that can support today's users and applications while preparing for a future where AI agents become another normal participant in business operations.
Take the Next Step: Modern Endpoint Management Review
Identity and endpoint posture are increasingly connected in Microsoft's Zero Trust model. L3's Modern Endpoint Management Review can help organizations evaluate device management, compliance, access controls, and the endpoint foundations that support secure Microsoft 365 and AI adoption.
