Quick Answer
Explore an eight-layer reference architecture for governed enterprise AI agents, covering agent identity, permissions, tool access, business rules, audit trails, human oversight, regulatory considerations, and lifecycle management. Learn how organizations can design accountable AI-agent workflows with enforceable controls and traceable decisions.
The governance challenge in agentic AI is that an agent can move from producing information to changing the business world. A system may look like a helpful assistant while using credentials to update records, initiate transactions, or trigger other software. Responsible governance must therefore cover more than model accuracy or a high-level acceptable-use statement. It must connect the business purpose to an enforceable authority boundary, create a trace of consequential actions, and preserve the ability to intervene.
This whitepaper proposes an eight-layer reference architecture for enterprise AI-agent governance. It is a logical design for discussion, not a deployed Intent Amplify software architecture, a certification standard, or a guarantee of legal conformity. NIST's AI Risk Management Framework provides voluntary governance and risk-management concepts [1]. ISO/IEC 42001 describes an organizational AI management-system approach [2]. Neither reference automatically validates the design or any particular implementation.
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