In a recent survey of 150 senior utility executives, nearly 40% of the respondents had already moved to advanced stages of AI deployment and 97% said they expect AI investments to increase over the next 3 years. But moving from a controlled pilot in a sandbox to scaled production on aging infrastructure requires more than a belief that AI can improve operations, decision making, investments, and grid reliability. Utilities are clear-eyed about the challenges. 92% say legacy system integration is a top barrier to AI adoption and 91% cite worries about AI tools hosted on public cloud infrastructure. This webinar answers practical questions about how to move AI from a promising abstraction to a beneficial reality and what utilities making the most progress have in common. It will address the: Pilot-to-production gap Challenges of legacy systems and data Importance of evaluating vendor infrastructure Reason why AI systems should be built on utility operational data, not general models
