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Predicting Risk: How Jaron Jones is Transforming Utility Services with AI
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In this Episode:
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Jaron Jones reveals how Elm stands apart by developing most of its operational software in-house—a rare feat in the utility services sector. By maintaining control over its tech stack, Elm can remain agile, secure, and innovative even with a system originally architected two decades ago. Jaron highlights how modernizing critical components in Azure while maintaining secure, decoupled legacy services allows Elm to balance innovation with stability.
Jaron dives into Elm's use of machine learning models to predict ticket risks and prevent potential damages before they occur. He explains how integrating GIS data—like the age of surrounding infrastructure and environmental details—adds critical context to their models, enhancing the precision of predictions. His approach underlines the real-world impact of AI and analytics on reducing costs, improving safety, and increasing operational efficiency.
Beyond the technical discussion, Jaron shares his personal story of entering tech unexpectedly—starting from hardware repairs and call center work while studying veterinary medicine. His story underscores the value of being adaptable, embracing unexpected opportunities, and continuously building skills. Jaron’s career journey serves as an inspiring blueprint for those looking to break into tech or climb the IT leadership ladder.
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