Root cause analysis often stops at “human error,” which is why the same incident types keep repeating. In this post, we explain how AI-assisted prevention mapping connects incident patterns to underlying system conditions by combining investigation data with frontline engagement signals and MCI-style trends. You’ll learn how to shift from blame to predictive prevention, use behavioral cohort insights to target interventions, and measure whether corrective actions are actually reducing repeat exposure.