Specifying the Delegated-Autonomy Boundary: Requirements Engineering for Agentic AI

2026-07-19

AI Summary

Existing requirements engineering approaches fail to explicitly define the scope of delegated decision-making, authorization hierarchies, oversight mechanisms, and control-relinquishment protocols in AI agent systems, often leaving critical requirements implicit in prompts or runtime policies. This work proposes the first requirements engineering framework tailored for autonomous agents, introducing the novel concept of “delegation autonomy boundaries” and modeling authority as a hierarchical structure. The framework specifies delegation behavior across six dimensions—purpose, authority, information, coordination, assurance, and evolution—through two complementary artifacts: Agent Justification Records (AJRs) and Agent Delegation Policies (ADPs). Empirical validation in hospital discharge coordination and automated code review scenarios demonstrates the framework’s effectiveness in enabling clear definition and management of delegation boundaries for both safety-critical and routine tasks.

Abstract

Agentic AI systems do not just predict or recommend; they plan, maintain state, and act in external environments with varying degrees of autonomy. This changes the requirements engineering problem in a specific and under-addressed way: it introduces what we call the delegated-autonomy boundary -- the set of decisions about what may be delegated to the system, under what graduated authority, with what oversight, and how control is returned. Current practices bury these decisions inside prompts, tool schemas, and runtime policies, even though they are requirements-level commitments. This paper proposes two complementary artifacts. First, an Agency Justification Record (AJR) helps teams decide when an agent is warranted over simpler alternatives. Second, an Agentic Delegation Policy (ADP) captures what must be specified for safe and effective development: purpose, authority, information, coordination, assurance, and evolution. Crucially, authority in the ADP is modelled as graduated, i.e., a tiered structure. We illustrate the framework with two contrasting examples: a safety-critical hospital discharge coordination agent and an automated code review agent.

Problem

• delegated-autonomy boundary
• requirements engineering
• agentic AI
• autonomy
• control delegation

Innovation

• delegated-autonomy boundary
• Agentic AI
• Agency Justification Record
• Agentic Delegation Policy
• graduated authority