What Is a Confidence Score?
A confidence score is a number, typically a percentage, that represents how certain an AI model is about its own prediction or decision. AI models often make judgments with incomplete or ambiguous information, and simply providing an answer without indicating the level of certainty can be risky for business decisions.
How it helps#
A confidence score provides a measure of reliability, allowing your team to automatically accept high-confidence predictions while flagging low-confidence ones for human review, thereby managing risk and improving efficiency.
How it works#
When an AI model analyzes data, it calculates the probability for each possible outcome based on the patterns it learned during training. For example, an AI processing customer support emails might calculate an 85% probability that an email is about a billing issue, a 10% chance it's a technical problem, and a 5% chance it's a sales inquiry.
The highest probability—in this case, 85%—is presented as the confidence score for its conclusion. This score is not a measure of absolute truth, but rather the model's internal assessment of how well the new data matches the examples it has seen before. A high score indicates a strong match, while a low score suggests the data is unusual or ambiguous and may require human attention.
How it is different#
A confidence score measures the model's certainty in a single prediction, while a metric like accuracy measures its overall performance across thousands of past predictions. An AI can have high overall accuracy but still produce a low confidence score on a specific, unusual case, correctly signaling the need for human oversight.