AI agent failure modes

Common AI Agent Failure Modes in Business Workflows

The most common AI agent failures in AAA.win are business risks: literal translation, unsafe promises, unsupported claims, and invalid structured output.

Best for: Operations, safety, compliance, and eval teams

Failures that matter in production

The most expensive failures are often not grammar mistakes. They are unsafe promises, invented fields, unsupported security claims, broken JSON, and local-language answers that sound unnatural.

  • literal_translation shows localization risk.
  • unsafe_refund_promise shows policy-boundary risk.
  • invalid_json and missing_field show automation risk.

How to read failure tags

Failure tags are audit leads. A tag count tells you where to inspect raw outputs, not where to stop thinking. High-risk tags should trigger human review and workflow-specific retesting.

Best next test

Build a small red-team set from your own support, writing, and extraction workflows. Include edge cases where the agent is tempted to promise too much or invent missing data.