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AI Support & Agents

Confidence Score

Definition

A confidence score is a value an AI system assigns to a prediction or answer that estimates how likely it is to be correct — used to decide whether the AI should act automatically, ask for clarification, or hand off to a human.

Also known as: confidence levelcertainty scoreAI confidence

How it works

Depending on the model and task, a confidence score can come from the probabilities behind a prediction (for classification like intent detection) or from heuristics and secondary checks layered around a generated answer. It's usually expressed as a number, often between 0 and 1 or as a percentage.

Support systems set thresholds on it: above a high threshold the agent answers or acts automatically; in a middle band it may ask a clarifying question; below a low threshold it escalates to a human with context.

Why it matters for support

Confidence scores are a core lever for safe automation. They let you tune how aggressive an AI agent is — resolving routine, high-confidence tickets on its own while routing uncertain ones to humans, so automation grows without sacrificing accuracy.

Frequently asked

Does a high confidence score mean the answer is correct?

Not always. Confidence estimates likelihood, not certainty — models can be confidently wrong. That's why confidence is used alongside grounding and guardrails, not as a sole guarantee.

How is a confidence score used in practice?

It's compared against thresholds to decide whether the AI answers automatically, asks for clarification, or hands off to a human agent.

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