When AI Automation Goes Wrong Six months ago, I consulted for an organization that had invested heavily in generative AI for their SOC—and nearly destroyed analyst trust in the technology. Their mistake? Treating AI as a black box that could replace human judgment. The fallout was spectacular: false positives skyrocketed, critical alerts were misclassified, and analysts began ignoring AI recommendations entirely. The promise of Generative AI Automation in security operations is genuine, but the implementation pitfalls are equally real. Having seen multiple enterprise deployments—some successful, others catastrophic—I've identified patterns in what goes wrong and how to avoid those mistakes. These aren't theoretical concerns; they're expensive lessons learned the hard way. Mistake #1: Deploying Without Validation Workflows The Problem: Organizations treat generative AI outputs as authoritative without establishing validation processes.…