Every IT team wants faster resolution and fewer escalations but giving AI the authority to take action in live environments introduces new risks. This session focuses on the operational realities of building safe, trustworthy auto-remediation pipelines. You’ll learn how leading organizations structure human-in-the-loop approvals, detect remediation loops, evaluate model reliability, and implement safeguards that prevent minor issues from escalating into outages. We’ll also explore the maturity curve toward self-healing systems and how responsibilities shift from engineers to AI as automation becomes more capable. Key takeaways: → How to design safe auto-remediation workflows with human oversight. → Techniques for identifying remediation loops and failure cascades early. → Frameworks for evaluating model reliability before allowing autonomous actions. → Guardrails that reduce operational risk as teams move toward self-healing systems.