AI Excessive Agency

Excessive agency in AI agents — over-permissioned tools, scope creep, and unchecked autonomy

9 patterns

Excessive agency in AI agents — over-permissioned tools, scope creep, and unchecked autonomy. We've tracked 9 distinct AI Excessive Agency patterns across production AI agent deployments — most commonly in Security, Task Planning, Operations systems. One recurring example: Excessive Agency — Agent Takes Actions Beyond Expected Scope

Each pattern below documents the specific failure mode, why it happens, and how teams have mitigated it in practice — use this page as a reference when building guardrails, writing evals, or debugging an agent that's already misbehaving in this way.

Related comparisons

Input Recursion Limit

Frequency:Occasional
Category:Operations

An agent's parser (JSON, XML, YAML, or a custom nested-structure format) receives an input with excessive nesting depth — either from a legitimately complex source, a buggy upstream serializer that loops, or a deliberately crafted payload — and the recursive-descent parsing logic exceeds the language runtime's call-stack limit or the parser's own recursion guard, crashing the process rather than rejecting the input gracefully. Because the crash happens inside the parsing library itself, it often takes down the whole request-handling worker rather than failing just the one bad input.

Over-Clarification

Frequency:Very Common
Category:Agent Interaction

The agent asks a clarifying question for a request that was already clear enough to act on, forcing the user through an unnecessary extra round-trip before getting the actual work done. Unlike clarification-loop-infinite, which is about a non-terminating sequence of questions, over-clarification can be a single instance: one avoidable question inserted into an otherwise straightforward request, driven by excessive caution rather than genuine ambiguity.

Stale Training-Corpus Fraud Typology Overrides Current SIU Red-Flag List

Frequency:Occasional
Category:Insurance

A Fraud-Detection Agent Screening Claims for SIU Referral Applies a Generic Fraud-Typology Pattern Absorbed During Pretraining (e.g., a Widely Discussed Staged-Collision Pattern or a Generic Soft-Tissue-Injury Red-Flag Profile) Instead of Querying the Live, Internally Maintained SIU Red-Flag List That the Carrier Has Available as a Tool, Missing a Recently Added Red Flag Specific to a Current Fraud Ring or Failing to Apply a Recently Retired Flag the Carrier Stopped Using Because It Generated Excessive False Positives