For the last 2 decades, Identity Systems have been built around a simple idea: behind every login, there is a person. AI agents are breaking that assumption.
An agent can log into apps, call APIs, move data, trigger workflows, and make decisions with real business consequences, often without a person approving every action.
That raises a basic security question: if an AI agent can act like a user, shouldn’t we manage its identity like one too?
AI Agents Are More Than Just Software
Traditional automation follows predefined instructions. An AI agent is different: it is given a goal and can decide how to achieve it, choosing from which tools to use to which systems to access.
That is useful, but it also makes agents harder to secure. Think of it like an employee with API access except the agent can work continuously, operate at great speed, and take more actions than a human.
This matters because non-human identities outnumber human identities in many enterprise environments. Existing IAM processes were not designed for identities that can be created, reassigned, or shut down within seconds.
What Goes Wrong When Agents Are Not Properly Governed?
The first problem is excessive access. Teams often give agents broad permissions “just in case” they need them. If that agent is compromised or manipulated, those permissions become part of the blast radius.
Credentials create a second risk. Many agent deployments still rely on long-lived API keys and shared secrets. Once those credentials leak, they can remain useful to an attacker for far too long.
Then there is prompt injection. Agents often read untrusted content such as webpages, emails, documents, and tickets. An attacker may be able to place instructions in that content and manipulate the agent into misusing permissions it already has.
That is why identity and authorization matter. Even if an agent receives a malicious instruction, it should still be limited in what it can actually do.
Compliance adds another reason to care. Regulators and auditors expect organizations to show who or what authorized an AI system’s actions and under what context.
Identity Gives Us a Control Point
Identity helps security teams answer 4 questions:
- Who is making this request?
- What are they allowed to do?
- Why are they doing it?
- Should they still have this access?
Those same questions should apply to AI agents. Every agent should have its own identity. It should not quietly reuse a developer’s credentials or simply appear as the employee who launched it. If an agent is acting on behalf of a user, the system should ideally know both identities: the user and the agent.
That matters for security, troubleshooting, and auditability. If an agent deletes a file, changes a configuration, or sends sensitive data, the organization should be able to determine which agent acted, who authorized it, and what permissions were used.
Zero Trust Fits AI Agents Well
Zero Trust is based on a simple idea: do not trust something simply because it was authenticated once. Evaluate each request in context.
That maps to AI agents as well. Instead of asking, “Can this agent access Salesforce?” A stronger question is, “Should this agent be allowed to read these customer records right now for this task?”
This pushes organizations toward task-specific access and short-lived credentials. If an agent needs database access for one workflow, give it a credential that works only for that agent, only for the required operation, and maybe expires when the task ends.
If the credential is stolen later, it is useless.
Start With Visibility and Ownership
Before an organization can secure AI agents, it needs to know they exist. Developers and business teams can deploy agents quickly, often without a security review or approval. That creates a new form of shadow AI.
Security teams need a clear inventory of agents, including who owns them, what systems they can access, what credentials they use, and whether they are still active.
Every agent should also have a named person or team responsible for its permissions, credentials, behavior, and eventual decommissioning. Without ownership, agents can easily outlive the project that created them and become another class of orphaned identity.
Least Privilege Has to Be Enforced
Least privilege cannot just exist as policy. It needs to be part of the architecture.
An agent should receive access based on the task it is performing, not every task it might perform someday. Requests for additional privileges should be visible and reviewable. Runtime monitoring matters too. An agent may technically have permission to access a resource but still behave suspiciously. An agent that normally reads a handful of customer records but suddenly attempts to download an entire database should trigger attention.
Static permissions tell us what an agent can do. Runtime monitoring tells us what it is actually doing. Both are necessary.
Agent Identity Needs a Lifecycle
Creating an identity is only the beginning.When an agent is created, its owner and permissions should be defined. When its responsibilities change, its access should change. When the agent is no longer needed, its credentials and permissions should disappear with it.
This is similar to the joiner-mover-leaver lifecycle used for employees, but it has to operate much faster. Quarterly spreadsheets and manual access reviews will not keep up with agents.
Where Enterprises Should Start
Organizations do not need to wait for every AI identity standard to be finalized.
Start by finding the agents that already exist and identifying what systems they can access. Assign a clear owner to each one. Then focus on the highest-risk agents, those connected to sensitive data, production infrastructure, customer systems, or financial workflows.
Reduce privileges, replace long-lived credentials with short-lived ones where possible, and make agent activity visible in existing security monitoring and audit systems. You do not need to redesign your IAM architecture on day one. Start with the agents that could cause the most damage.
Identity Will Become Part of the AI Control Plane
AI agents can make decisions, choose actions, interact with multiple systems, and operate at a speed humans cannot match. The question is no longer just whether an agent can authenticate. Organizations need to know which agent is acting, who it is acting for, what it is allowed to do, and whether that specific action should be permitted right now.
Companies that solve those questions early will have a much easier time scaling agentic AI safely. Those that treat identity as something to add later may eventually discover that they have hundreds or thousands of autonomous identities with permissions nobody fully understands.
References
- MSSP Alert, “Security Teams, MSSPs Will Wrestle with Agentic AI, Non-Human Identities in 2026” — https://www.msspalert.com/news/security-teams-mssps-will-wrestle-with-agentic-ai-non-human-identities-in-2026
- Forrester, “Identiverse 2026 Recap: Identity Security For Agentic AI Dominates” — https://www.forrester.com/blogs/identiverse-2026-recap-identity-security-for-agentic-ai-dominates/
- CSO Online, “Agentic AI identity: A 6-stage maturity model for non-human identities” — https://www.csoonline.com/article/4194548/agentic-ai-identity-a-6-stage-maturity-model-for-non-human-identities.html
- Cloud Security Alliance, “The Non-Human Identity Governance Vacuum” whitepaper (2026) — https://labs.cloudsecurityalliance.org/research/csa-whitepaper-nonhuman-identity-agentic-ai-governance-v1-cs/
- NHIMG, “How should teams govern non-human identities as AI agents scale?” — https://nhimg.org/community/nhi-events-forum/how-should-teams-govern-non-human-identities-as-ai-agents-scale/
- NHIMG, “Machine Identity Management Trends for 2026” — https://nhimg.org/nhi-101/machine-identity-management-trends-2026
About Anirban Mukherji:
Anirban Mukherji is the Founder and Chief Executive Officer of miniOrange, a global identity and access management and cybersecurity solutions provider serving 25,000+ customers across 60+ countries. With nearly two decades of experience in security engineering and product leadership including senior roles at IBM and RSA Security, he drives innovation in secure digital transformation, IAM and AI-ready security frameworks. At the India AI Impact Summit 2026, he is championing India’s potential to become a global cybersecurity and AI backbone. He is specialized in Global Cybersecurity (IAM, PAM, IGA, UEM, Data Privacy, AI & Enterprise Security).
About miniOrange:
miniOrange is a global cybersecurity company specializing in Identity and Access Management (IAM), Single Sign-On (SSO), Multi-Factor Authentication (MFA), and identity governance solutions. Founded by Anirban Mukherji, the company provides secure authentication and access management products that help enterprises protect digital identities, applications and data across cloud and on-premise environments.
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