Privileged Access Management may already be the most mature security framework available for governing what AI agents can do in production environments, according to an analysis published by Security Boulevard on Friday. The argument: an AI agent that acquires credentials, calls APIs, accesses databases, and executes commands is performing exactly the privileged operations that PAM infrastructure was built to manage for human operators. Rather than building agent-specific security tooling from scratch, enterprise security teams can extend existing PAM concepts like Just-in-Time (JIT) access, least-privilege enforcement, machine identity management, and Zero Trust architectures to cover non-human identities (NHI).
Where PAM Fits in the Enterprise Agent Stack
This week has produced four distinct enterprise agent governance announcements: SandyClaw for skill-level testing, Chromia’s Atbash for blockchain-backed policy enforcement, Nuggets Labs for liability governance, and now PAM as the identity and access control layer. A pattern is emerging. Enterprise buyers aren’t waiting for a single vendor to build an end-to-end agent governance platform. They’re assembling the stack from existing security infrastructure and new purpose-built tools. For teams building agents that need to pass enterprise procurement, the practical implication is specific: frame agent permissions using the vocabulary security teams already understand. JIT access, least-privilege scoping, and NHI management aren’t new concepts to your customer’s CISO. They’re the concepts that will get your agent approved.