Context: In utility operations, non-technical loss is not caused by weak detection or poor data, it reflects execution that fails to convert signals into timely action.

Challenges: Irregular consumption is flagged but not prioritized, site inspections are scheduled weeks later, and field findings don't translate into timely correction, enforcement, or billing recovery, so revenue is already gone by the time cases are closed.

Solution: The Non-Technical Loss Guidance Agent, an AI agent built using Microsoft Copilot Studio, monitors suspected loss cases as they are flagged and intervenes during field inspection and billing correction, flagging cases where delay carries real revenue risk before the recovery window closes.

Impact: Utilities following this approach see cases move from detection to resolution without delay, with loss declining as an outcome of discipline, not effort.