The Mechanisms of AI Harm

As AI systems become woven into everyday decision-making, real incidents are revealing how quickly benefits can give way to harm when models fail, are misused, or are deployed without proper oversight. This report breaks down six pathways through which AI causes damage, from intentional misuse to subtle integration failures that emerge only once a system is embedded in the real world. The findings show that harm is not limited to advanced models—simple, single-purpose tools can be just as risky depending on how they are designed and governed. Understanding these patterns is essential for building smarter safeguards and deploying AI responsibly across sectors.