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Every reliability engineer knows the component that fails in service because nobody checked it at receiving inspection. Power system studies belong on that list. A specification calls for power flow with voltage drop, short circuit and arc-flash analysis. A study group delivers a report, the report goes to the customer, and far more often than not it sits in the contract papers until something happens.

Ask most facilities how often their electrical assets receive a thermal imaging inspection and the answer is annual. Ask why annual, and the answer is usually that it has always been annual, or that the insurer or an auditor expects to see a yearly certificate. Neither is an engineering answer. Annual-by-default is a calendar decision wearing an engineering costume, and on some assets it is too often, on the ones that matter most it is nowhere near often enough.

Utilities are under pressure to deliver safe, reliable, affordable and lower-carbon services while managing ageing networks, capital programmes, workforce constraints, cyber exposure and increasingly complex operating conditions.

AI can help utilities detect weak signals, predict failure risk, prioritize interventions and improve planning. But a prediction does not create value by itself. Value appears only when the insight reaches an accountable operational decision, becomes safe and executable work, and produces an outcome that can be measured.