Judgment Delegation Protocols for Agentic AI Systems From Best-Practice Checklists to Observable Responsibility Chains

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.