Utilities operate some of the most complex sociotechnical systems on the planet. Generation, transmission, and distribution networks generate petabytes of heterogeneous data every day, yet much of it remains locked in SCADA historians, scanned regulatory filings, and decades-old maintenance logs. Large language models offer a genuine path out of this paralysis, not by replacing existing control systems, but by making unstructured data actionable and by accelerating decision loops that currently depend on manual review. The shift is already beginning. Forward-looking grid operators are using LLMs to summarize incident reports, extract compliance constraints from hundred-page tariffs, and draft work orders from noisy field notes. The challenge is not whether language models are relevant to utilities, but how to deploy them without letting inference costs scale out of control as prompt
