Imagine an AI agent in your enterprise making autonomous decisions – moving data, accessing sensitive systems, or executing transactions – without human oversight. Now imagine it doing so without a verifiable identity. How do you know you can trust it? Traditional credentials like API keys or passwords aren’t enough when AI acts independently.
Without cryptographic proof of identity, every agent could become a potential security gap. In this post, we’ll explain how public key infrastructure (PKI) can bring cryptographic trust to agentic AI. This piece builds on our previous discussions, where we introduced the rise of Agentic AI as well as the opportunities and risks for businesses today. Together, these insights lead naturally to understanding Keyfactor’s new capability, which brings cryptographic trust to AI agents in enterprise environments.
Here’s what you need to know:
Every AI Agent Gets a Strong, Verifiable Identity
Traditional credentials like API keys or client secrets aren’t enough for autonomous AI systems. Keyfactor issues unique X.509 certificates to each AI agent, giving them cryptographically-backed, non-replicable identities. This ensures accountability and prevents agents from becoming security weak points, even short-lived ones created for a single task.
Zero Trust Principles Extend to AI Communications
Keyfactor integrates certificate-based OAuth flows and mutual TLS (mTLS), so AI agents can securely communicate with services and other agents. Policies embedded in certificates define which systems an agent can access and what actions it can perform. This layered approach brings Zero Trust governance to AI at enterprise scale.
Security and Compliance at Scale
Automated certificate lifecycle management allows enterprises to deploy thousands of AI agents without manual overhead. Every action an agent performs is cryptographically attributable to a specific agent, reducing risk while supporting compliance in regulated environments. This unlocks the potential for AI in sensitive or high-stakes applications while maintaining oversight.
With this PKI-backed approach, enterprises can safely scale autonomous AI while staying secure, auditable, and compliant.
As Ellen Boehm, SVP of IoT and AI Identity Innovation at Keyfactor, explains:
“Organizations are eager to scale AI agents, but they face a new identity crisis — one where static credentials like API keys and client secrets simply don’t provide accountability or security. With Keyfactor’s PKI foundation, AI agents gain the same strong, auditable identity as humans and devices, enabling enterprises to embrace AI safely and in line with Zero Trust principles.”
How It Works
Keyfactor’s approach applies proven PKI and certificate lifecycle automation to agentic AI environments:
- Cryptographic Identity: Each AI agent is issued a unique X.509 certificate, creating a verifiable, non-repudiable identity that cannot be forged or accidentally shared.
- Certificate-Based OAuth Flows: Instead of relying on static secrets, OAuth tokens are anchored to client certificates, ensuring actions are securely tied back to a specific agent or user.
- Mutual Authentication: AI-to-service and agent-to-agent communications are protected with mutual TLS, allowing both sides to verify identity before sharing data.
- Automation at Scale: For containerized or short-lived AI agents, Keyfactor integrates with SPIFFE to automatically assign, rotate, and revoke certificates with zero manual effort.
- Policy-Driven Control: Certificate extensions define what systems an agent can access, what operations it can perform, and when, providing built-in governance and auditability.
This layered approach extends Zero Trust principles to environments where AI agents operate, enabling organizations to deploy thousands of autonomous or semi-autonomous agents without sacrificing security, compliance, or oversight.
The Road Ahead
As AI continues to take on more autonomous roles, ensuring that every agent’s actions are verifiably secure is essential.
PKI-secured agentic AI delivers cryptographic accountability, regulatory readiness, and operational scalability, empowering organizations to unlock sensitive and regulated AI use cases with confidence.
Gartner underscores the need for workload-bound identities over human-focused MFA. According to Gartner research, “Using MFA works great for humans but is not appropriate for workloads, such as AI agents. Instead, consider using workload identities or credentials, such as workload-bound certificates.”
Take the next step: explore Keyfactor’s recent whitepaper, Securing Agentic AI with Zero Trust, and learn how Keyfactor solutions can help you secure, scale, and confidently deploy AI agents across your organization.
