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From Utility Data to Operational Action: Privacy‑Honoring, Governed, Purpose‑Built Agents on an AI‑Ready Foundation
Utilities want agentic capabilities that improve daily work: faster triage, consistent investigations, reliable reporting, and guided decision support. However, those outcomes depend on whether operational and enterprise data is trustworthy and usable across systems. This session explains how to turn fragmented utility data into an AI‑ready operational foundation: consistent definitions, identifiers, timestamps, traceability, and the context needed to reason across events, outages, assets, alarms, logs, and procedures.
We then connect that foundation to purpose‑built agents deployed in a closed, utility‑controlled environment (on‑site or tenant‑isolated), where data privacy policies, role‑based access controls, and governance requirements remain in force. Rather than “plugging in” open AI, we focus on operationally-scoped agents that retrieve only what they need for approved tasks and produce traceable outputs, so utilities can scale agentic workflows without compromising governance or trust.
Attendees will learn a practical checklist for making operational data AI‑ready, how to distinguish missing data from missing context, and how to design governed, purpose‑built agents that operate in a closed utility environment with least‑privilege access and traceable outputs enabling repeatable, operationally safe agentic workflows with humans in control.
Speakers
