Agentic AI growth is exploding, as organizations tap autonomous, goal-driven systems to drive huge gains in efficiency. Organizations are adopting AI agents for intelligent services, shifting focus from isolated tasks to end-to-end coordination.
AI agents are seeing the most growth in customer service, where they enable more proactive, personalized support. The finance industry is using agentic AI for intelligent fraud detection, while the manufacturing sector is using it for predictive maintenance and complex problem-solving. Cybersecurity is an important application, with AI agents enforcing policies and detecting anomalies in real time.
However, the influx of AI agents is creating identity and access management risks. AI agents need identities to interact with other systems within the IT environment. However, their nature makes them fundamentally different than human and traditional machine identities.
Unlike service accounts or API keys, agentic identities are capable of making independent decisions and taking actions across diverse digital environments. They can reason, plan and execute multistep tasks without constant human intervention. While traditional machines are deterministic, agentic AI behavior is less predictable, requiring real-time, context-aware authorization rather than fixed roles.
AI agents pursue objectives, potentially across multiple systems, requiring complex authorization. As a result, agentic AI identities are by nature fluid. Access needs change dynamically based on the task, requiring granular, just-in-time permissions. Additionally, AI agents often act on behalf of a human user or another system, requiring a verifiable “chain of intent” to ensure every action can be traced back to its origin.
The ephemeral nature of AI agents also requires a new approach to identity management. Agents are often created on demand for a single task and destroyed within seconds, making static, long-lived credentials a security risk.
Organizations face significant risks if they fail to manage agentic identities properly. Because of agentic AI, machine identities are projected to outnumber human users by as much as 80:1 in the coming year. AI agents are often granted excessive permissions to avoid blocking functionality. However, granting broad access to powerful AI agents creates a large attack surface.
What’s more, many of these AI agents are being created outside official IT oversight. Ungoverned agentic AI identities can accumulate excessive privileges, creating invisible entry points for attackers. Hard-to-track shared credentials and delegated actions obscure who (or what) is responsible for a security incident.
Traditional identity models struggle to track and govern these independent actors. They are designed to manage persistent users, fixed roles and human-like interactions. AI agents initiate their own goal-oriented activities, bypassing standard approval workflows. Real-time, autonomous actions across multiple systems overwhelm traditional monitoring tools, hiding risky behavior.
Agentic AI requires new identity frameworks to manage the potential risks across complex systems. It’s about proving what the AI agent is, what it’s allowed to do, and who controls it, ensuring accountability.
Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs) offer a means of managing identities and securing autonomous interactions. A DID is a unique identifier that points to a cryptographically signed document, giving an agent a verifiable presence. A VC is cryptographically secured digital proof, linked to a DID, that confirms an agent’s capabilities, qualifications or permissions.
SPIFFE (Secure Production Identity Framework for Everyone) is an open standard that also uses decentralized identifiers and signed credentials to prove an agent’s identity and permissions. Model Context Protocol (MCP) is a new universal interface that allows agents to connect securely to various tools and data sources with consistent identity oversight.
Agentic AI identity management remains a new discipline, and few organizations have expertise in this area. Technologent is here to help you determine the right strategy to secure AI agents across the enterprise.