Workload Automation Re-imagined with AI-based Analytics discusses how modern IT complexity has reshaped traditional workload automation. While automation tools are widely adopted, the focus has largely remained on scheduling and monitoring, leaving workload analytics underutilized. As environments grow more complex with multiple schedulers, dependencies, and infrastructures, limited visibility makes issue detection and optimization difficult. The document explains how AI-based intelligent analytics complements automation by providing predictive insights, anomaly detection, and root-cause analysis. It introduces ignio AI.Workload Management, highlighting capabilities such as intelligent workload analytics, proactive operations, and extending value beyond batch jobs to support more resilient

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