Industry
Power, gas and water utilities and energy retailers: billing, outage communication, field work and grid operations.
30 organizations in 13 countries run these use cases in public. 65% of those 31 deployments disclose a measurable outcome.
A voice and messaging agent that contacts customers in early arrears to collect payments. It answers their inbound calls too, takes payments and sets up payment arrangements within preapproved rules, and recognises signs of hardship or vulnerability so those customers go straight to a trained person.
An AI agent for utility billing and moves explains bills and tariffs, takes meter readings and manages payments and account moves for energy and water customers. It also handles move in and move out, including final reads and closing one account and opening the next, across phone, messaging, email and the app, while anyone in payment difficulty, in a vulnerable situation or with a complaint is handed to a person.
Smart meter analytics is AI that turns readings from smart electricity, gas and water meters into usable information for utilities, instead of treating every meter and customer the same way. It monitors meter and network health at scale, estimates which appliances drive a household's usage from the meter signal alone, flags unusual consumption, and targets efficiency and electrification programmes at the customers who will benefit most.
AI supplier invoice processing is AI that captures supplier invoices in any format and extracts the header and line data. It matches invoices to purchase orders and goods receipts, proposes tax and cost centre coding, flags duplicates and suspected fraud, and routes them for approval and posting, leaving only exceptions to accounts payable staff.
Renewable generation forecasting is AI that predicts how much power a wind or solar asset will generate over the next hours to a day ahead. It combines weather forecasts with historical turbine or panel output, so a grid operator or generator can commit to a delivery schedule instead of treating renewable output as unplannable.
AI predictive maintenance is machine learning that learns the normal behaviour of industrial and energy equipment and flags early signs of degradation before a failure. It works from sensor and process data, flags issues weeks or months ahead, and turns them into prioritised maintenance work, so plants and utilities plan repairs instead of reacting to breakdowns.
Call quality and compliance monitoring is automated quality assurance that transcribes and scores every customer interaction, voice and chat, against the organization's own rubric. It checks required disclosures and script adherence, flags conduct and mis selling risk, and surfaces coaching opportunities, instead of the small sample a human QA team can review.
Sales quote and estimate generation is AI that turns a customer's product list, drawing, roof photo or request for quotation into a draft quote for a seller or estimator. It reads the input, matches items to the catalog, calculates quantities and applies the organization's price rules, and the seller or estimator then checks and sends it.
AI storm outage prediction is AI that predicts how many outages a coming storm will cause, where, and how severe restoration will be, for utility storm response teams. It combines weather forecasts, historical outage records and network data, so a utility can stage crews and mutual aid before the storm arrives instead of assessing damage after it hits.
Power line vegetation management is AI that analyses imagery of the land along power lines to estimate where vegetation risks the lines, for utility crews. It uses satellite, aerial or lidar imagery to judge how fast vegetation will grow into the lines or fall onto them, and turns that into a risk based trimming and hazard tree removal plan, replacing fixed trimming cycles and manual patrols.
Free PDF playbook
10 use cases with deployments, value, playbooks and governance, in one document for your team.
Computed from the 31 public deployments behind these use cases at energy and utilities organizations. Numbers update with every checked record.
26 public deployments at 26 organizations outside energy and utilities run these use cases too. They are not counted in the numbers above; each use case page shows them.
