AI is about far more than chatbots and copilots. For utilities, the bigger opportunity may be in applying purpose-built models to the operational data from smart meters, customer systems, weather, outages, and grid equipment.
In this first episode of a four-part series with Bidgely, Stephen Lacey talks with Venkata Nimmala, director of digital transformation and enterprise architecture at Arizona Public Service, and Karthik Moorthy, chief growth officer at Bidgely.
APS initially partnered with Bidgely to solve a highly practical customer-service problem: helping call-center agents explain why a customer’s bill had increased. By using appliance-level energy disaggregation, the utility moved beyond generic explanations to identify the likely drivers of higher usage.
But the project soon raised a bigger question. How could the same intelligence support a wider range of planning and operational solutions across the utility? Venkat and Karthik explain how APS began bringing Bidgely’s models closer to the utility’s own data environment, creating a foundation for broader experimentation and deployment.
They discuss data sovereignty, centralized AI governance, the difference between buying a point solution and building deeper capabilities, and why AI transformation is ultimately as much about data and operating models as it is about technology.
This is partner content, brought to you by Bidgely. Learn more about how Bidgely works with utilities through its UtilityAI platform.
