
This working paper proposes judgment delegation protocols as a missing governance layer for agentic AI deployments. It translates high-level best-practice guidance into auditable governance primitives: delegation events, authority states (advisory → relied-upon → authoritative), override conditions, and responsibility anchoring across socio-technical nodes. Rather than regulating model internals, the framework makes responsibility chains observable and contestable at the workflow level—where judgment most often migrates silently and accountability collapses without error.
agentic AI; AI governance; judgment delegation; responsibility chains; auditability; workflow governance; authority drift; contestability
agentic AI; AI governance; judgment delegation; responsibility chains; auditability; workflow governance; authority drift; contestability
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