We’ve seen AI work well in a workflow and still make the process worse

Integrating AI into workflows can sometimes worsen processes, even when the model performs well. A key challenge arises when AI systems make errors, for example, 10% of the time. If there isn't a clear method to flag, review, or reroute these incorrect cases, teams face an additional management burden. The question for those using AI in production is how to handle situations where the model lacks confidence.

Unlike typical discussions on AI model performance, this report focuses on the often-overlooked challenge of managing the 10% of cases where AI gets it wrong, rather than just model accuracy.