Advances in AI and generative AI have revolutionized predictive maintenance, making it more accessible, actionable, and scalable across industrial environments. Traditional maintenance strategies often rely on static sensor thresholds, leading to false positives and negatives, increasing costs and allowing critical failures to go undetected. AI overcomes these limitations by continuously learning from sensor data, historical failures, and operational conditions, identifying early warning signs with greater accuracy than human-defined rules. At Fiix by Rockwell Automation, the development of Fiix Asset Risk Predictor (ARP), Fiix Prescriptive Maintenance, and Fiix Maintenance Copilot has leveraged AI for early failure detection, prescriptive analytics, and automated workflows. AI detects anomalies and degradation patterns in equipment before issues escalate, minimizing unplanned downtime. It provides root cause analysis and precise maintenance recommendations based on past interventions, seamlessly integrating insights into your CMMS to trigger work orders, predict spare parts requests, and alert technicians.