A false negative in A/B testing refers to a situation where a test incorrectly concludes that there is no significant difference between two versions of a product or process, when in fact there is a difference. This can occur when the sample size is too small or when the test is not properly designed, leading to a missed opportunity for improvement. It is important to minimize false negatives in A/B testing in order to accurately assess the effectiveness of changes and make informed decisions for optimization.