This session explores how AIOps AI for IT and Operations is being applied in healthcare to automate, monitor, and optimize clinical and operational workflows, driving measurable improvements in care, safety, and efficiency. Through real-world deployments, we’ll highlight practical AIOps principles in generative AI and LLMs: Boost Medical Group uses AI to extract diagnostic codes from unstructured records for legal and claims workflows integrated with EHRs like AdvancedMD and legal databases, with medical validation reducing errors. Sama Therapeutics deploys AI agents for conversational psychometric assessments in behavioral health, combining language and digital biomarkers to reduce readmissions (15–20%) and speed up diagnosis (30%), applied in clinical trials and everyday care. We’ll examine core AIOps strategies adapted for healthcare: high-quality data pipelines to reduce bias, human-in-the-loop and “bot vs bot” checks to minimize hallucinations, API-first system integration, and continuous monitoring for safety. Finally, we’ll explore scalable stacks that are foundation-model-agnostic, apply GenAI tools like OpenAI APIs and video, and focus on rigorous doctor-vs-AI validation showing how AIOps supports safe, high-impact AI across complex clinical environments.