Mentioned in 51 AI use cases across 7 industries
AI watches heat and power-use data from electrical systems to catch dangerous overloads before they cause outages or fires.
The system groups customers by how they use energy and helps utilities send the right efficiency tips or programs to the right people.
When a market trade happens, the system instantly recalculates the plant’s schedule and sends the new instructions to the plant control system so the plant can actually deliver what was traded.
One meter sends trusted energy and power-quality data into utility control systems using standard substation languages, while locking down who can change settings.
Instead of sending sensitive transformer data everywhere, the analytics can run on a separate local network so operators get AI-driven insights with lower cyber risk.
Instead of compressors acting like isolated machines, they share data with the rest of the factory so operations and energy use can be coordinated better.
Use software to decide when pumps, storage tanks, and treatment assets should run so a city still gets water but uses less energy.
AI can act like an energy conductor, deciding how to use solar power, geothermal energy, and heat pumps so the building wastes less energy and can send extra power back to the grid.
Sensors watch the grid all the time, and AI spots signs that equipment may fail soon so crews or automation can act before the lights go out.
Use one network model to turn utility asset data into engineering designs, schematics, maps, and views that different teams can use without rebuilding the data each time.
The utility replaced paper and many disconnected tools with one outage system plus mobile apps so office staff and field crews can see the same outage information and coordinate faster.
Sensors watch water pressure in the network and a controller tells pumps to slow down or speed up so customers still get water without over-pressurizing the pipes.
An AI copilot helps power grid operators read procedures, think through what to do next, test options in a grid simulator, and suggest the safest or best action.
Before AI can help the grid, utilities need all their scattered data in one understandable place. This workflow gathers and organizes that data so AI apps can learn from it and operators can see the full picture.
Equipment in a data center can tell operators when it is unhealthy before it fails, so teams can fix problems early instead of waiting for outages.
AI helps the mills react better to changing material properties so they grind cement more efficiently and waste less energy.
AI watches how materials and production streams move through a plant and suggests better settings so the factory wastes less and runs more smoothly.
An AI system watches how a factory or commercial building uses electricity, predicts what energy it will need next, spots waste, and suggests or makes adjustments so the site uses less energy without hurting operations.
Ameren Illinois uses an APM system to combine data about substations and transformers so it can spot which equipment is most likely to fail and fix the riskiest ones first.
Customers can check a map or portal to see where the outage is and when power may return, instead of calling the utility for updates.
A central platform collects data from pumps, motors, drives, and sensors, then turns it into recommendations and automation that help the whole station run better.
Albemarle created many reusable equipment templates and dashboards so engineers spend less time digging through data and more time improving the plant.
Use machine learning to watch how power-industry machines behave and warn teams before a breakdown happens.
The system watches harmonic distortion levels and warns when they are likely to cross accepted limits, helping the facility stay within power-quality rules.
The company tracks how much solar power it makes and uses, and how much water gets recycled, so it can waste less and hit sustainability goals.
The software helps utilities prepare and track the exact switching steps needed to safely disconnect equipment, create safety zones, authorize work, and keep a full audit trail.
A digital twin brings together data from renewables, electrolyzers, and storage so operators can continuously tune the whole hydrogen system to cut waste and cost.
The utility can now see outage patterns in much finer detail, almost like tracing where the worst part of a storm traveled, so crews and planners can respond better and learn from each event.
A dashboard looks at meter history and weather-related conditions to find transformers that were overloaded before and warns which ones may overload again, so utilities can upgrade them before customers lose power.
AI acts like a smart conductor for the whole hydrogen plant, coordinating energy use and operations so the plant runs cheaper and more smoothly.
An AI system watches how a cement mill is running and continuously adjusts controls so the mill makes more cement with more consistent quality than a human operator alone.