A new identity class: Why AI agents require runtime control

AI agents help enterprise operations move beyond simple automation to autonomous decision-making and action execution. But unlike traditional software bots, AI agents are digital actors capable of operating independently because they can reason, plan, and interact dynamically with systems and users.

Because of these qualities, AI agents fall between human identities and traditional machine identities. They are an entirely new identity class that requires governance models designed specifically for agentic behavior.

Traditional identity and access management (IAM), privileged access management (PAM), and API security controls were designed for static applications and predictable user behavior.

AI agents, however, continuously adapt their behavior according to context, chain decisions autonomously, and interface with multiple systems in real time — all actions that can create significant risks and which cannot be governed using static permissions and login-time authorization alone.

Runtime-first identity controls are essential to making certain that AI agents operate within policy, maintain accountability, and do not become overprivileged attack surfaces.

"Enterprises need to ensure that every AI agent operates under its own identity — never a human's — so that every action is accountable and governed," says a recent Ping Identity eBook. "Trust in the agent economy begins with identity."

The four classes of AI agents and how identity differs for each

Ping Identity identifies four broad categories of AI agents, each requiring distinct identity and governance approaches.

The first is the personal agent. These are user-owned assistants that act externally on behalf of individuals, such as travel planners, shopping agents, or tax-preparation assistants. Because they operate outside enterprise trust boundaries, organizations must authenticate personal agents as separate identities while securely verifying delegated authority from the user.

The second category is the digital assistant for consumers. These enterprise-managed agents interact directly with customers in the form of chatbots, banking assistants, or service agents. Because digital assistants for consumers may access sensitive customer information or initiate transactions, they require enterprise-issued identities, scoped permissions, and auditable activity logs.

Third are workforce digital assistants that operate internally to support employees. These agents may automate HR requests, onboarding tasks, or financial workflows. Because they operate within enterprise trust boundaries, they require governance similar to that of workforce identities, including role-based access, continuous monitoring, and auditability.

Finally, digital workers represent the most autonomous class of AI agents. These execute complex business processes such as inventory management, compliance monitoring, and multi-system orchestration. Their high degree of autonomy makes persistent, verifiable identity essential to maintaining accountability and operational control.

Why runtime authorization is critical to governing agentic AI actions

Traditional IAM systems rely heavily on static roles, long-lived credentials, and login-time authentication. But these approaches are not enough to govern AI agents because agentic behavior is dynamic, contextual, and continuous.

Runtime authorization evaluates every action an agent takes in real time against current context, risk, task intent, and delegated authority. This approach is necessary because AI agents can make decisions independently and rapidly escalate privileges or interact with sensitive systems without human intervention.

Ping Identity emphasizes four foundational principles for governing agentic identities:

Sharing of static, long-lived credentials is very risky because it breaks auditability and lets agents impersonate users directly. Instead, agents should be granted scoped, short-lived delegated access tokens tied to specific tasks and policies.

Runtime controls also support adaptive authorization. Rather than granting permanent access, you can continuously evaluate whether an agent should proceed based on risk signals, behavioral patterns, timing, and operational context.

How to evolve your identity strategy to mitigate the risks of agentic AI

To govern AI agents effectively, you must take your identity strategies beyond human-centric IAM. Treat AI agents as first-class digital identities that require lifecycle management, ownership assignment, and continuous monitoring.

Start by inventorying and classifying all AI agents across the environment. Each agent must get a distinct identity, a responsible owner, and clearly defined operational boundaries.

Procedures such as Dynamic Client Registration (which lets AI agents register as OAuth clients), OAuth 2.0 delegation, scoped access tokens, and mutual TLS authentication can provide mechanisms for secure onboarding and runtime verification.

Implementing continuous behavioral monitoring is equally important. AI agents introduce or expand attack surfaces, including credential misuse, overprivileged access, adversarial manipulation, and shadow agents operating outside governance controls. Runtime telemetry, anomaly detection, and automated kill switches will help you contain compromised or misconfigured agents before damage can spread.

Make sure that human oversight remains part of the control framework. For high-risk or irreversible actions, require human-in-the-loop approvals and step-up authentication to ensure accountability.

AI agents are now operational participants within enterprise ecosystems. Securing them requires moving from static access management toward runtime identity governance that continuously evaluates trust, context, and risk. Organizations that modernize identity strategies for agentic AI will be better positioned to scale innovation securely while maintaining visibility, accountability, and control.

"AI agents are already acting on behalf of your users," says the Ping Identity eBook. "Make sure your identity strategy — and your trust framework — are ready."