Mentioned in 1 AI use cases across 1 industries
Instead of waiting for something like HVAC or plumbing to break and upset tenants, AI predicts failures early and automatically creates preventive work orders.
A chat-based AI helps field and maintenance teams ask plain-language questions about equipment, maintenance, and reliability data, then returns answers through a dynamic dashboard.
The company tests hypothetical changes—like different offers or service improvements—to see which actions might keep a customer from leaving before spending money on them.
Workers or drones take pictures of equipment, AI checks the images for wear or damage, and the system creates alerts or maintenance work automatically.
A utility keeps a digital record of each field asset, tracks what happens to it, and updates its status as work is done so teams know where equipment is and what condition it is in.
Instead of employees manually deciding what to do with every suspicious meter alert, the system automatically opens, filters, routes, and closes investigation cases based on predefined rules and statuses.
A utility software vendor provides a centralized online guide hub so teams can find product documentation, videos, API references, and help for managing utility work and assets.
An AI system watches factory equipment data to spot signs of wear or failure early, like noticing a machine is starting to get sick before it breaks.
When a utility plans a job, this setup can connect the job to purchasing, inventory, accounting, and the crew that actually does the work.
Maintenance data is sent into company dashboards so finance, operations, and maintenance can all see the same numbers and make better decisions.
An AI controller estimates the best operating point for a tidal turbine without relying on direct flow-speed sensors, so the turbine can keep harvesting as much energy as possible from changing tides.
A map-based mobile app tells tree-trimming crews exactly where to go, what work ticket to complete, and lets managers see progress live instead of relying on paper maps and forms.
When a utility customer issue needs work on physical equipment, the billing/customer system can pass that service call to an asset management system so field and asset teams can act on it.
An AI tool learned from one WM patient’s own treatment history and blood test results to suggest how much Ibrutinib he should take over time, instead of relying only on a one-size-fits-all dose.
Utilities connect their maps, work orders, and asset databases so everyone sees the same asset details and discrepancies can be found during inspections.
AI can study failure codes and past repairs tied to each asset to find patterns, helping teams adjust maintenance tasks and frequencies before repeat failures happen.
Put all asset and work information in one place so managers can decide what to fix first, who should do it, and how money should be spent based on facts instead of opinions.
Instead of crews writing things down later or using separate systems, workers can enter time and substation job details on mobile tools while in the field, making records faster and more accurate.
LP Building Solutions uses Syncron Warranty like a smart digital claims desk that helps organize, process, and connect warranty claims faster across customers, dealers, and suppliers.
The utility built a live digital copy of its equipment so it can spot which assets are likely to fail and fix them before they cause outages.
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.
The plant uses AI and digital monitoring tools to spot equipment and structural problems early, so teams can fix issues before machines fail or production slows down.
Use machine learning to watch how power-industry machines behave and warn teams before a breakdown happens.
Oil lab reports used to sit in email. The system now reads them automatically, links them to the right machine, compares them with temperature and vibration trends, and creates a repair job when the combined evidence shows wear.
Amazon uses AI to watch machine behavior, spot signs of trouble early, and help teams fix equipment before it breaks.
Utilities keep asset, maintenance, and inventory information in many systems. This partnership combines asset-management consulting with master-data tools so companies can clean up that information and make better operating decisions.
A software system helps utilities keep track of important equipment and infrastructure, like a smart filing cabinet and workflow hub for physical assets.
A technician uses one mobile app to see customer details, outage history, manuals, capture photos and signatures, order parts, and update job status instead of using paper and phone calls.
An AI assistant helps the new building owner receive the right logins, manuals, training, and system information so they can run the building from day one.
A chat assistant is added around Maximo so workers can ask plain-language questions about maintenance and asset management and get useful answers.
Instead of every mechanic doing paperwork, planning, material gathering, and coordination alone, assign one person to plan and schedule so the others can spend more time actually fixing equipment.
The system keeps a detailed card for each warranted piece of equipment, including where it is, what it is, who covers it, and how to contact them.
Machines send live readings to the maintenance system, which can trigger service when conditions show trouble instead of waiting for a fixed calendar date.
When the system detects signs of equipment trouble, it automatically alerts maintenance teams through the tools they already use so issues can be handled faster.
When AI figures out what is likely wrong, it can help managers make sure the right parts are available and required rules are followed.
The utility used a structured asset management system to prove to regulators that it runs the network reliably and cost-effectively, helping avoid penalties and earn incentive rewards.
Evergy turned inspection photos and defect findings into a smarter way to decide which power-grid equipment needs money and attention first.
AI reads labels on utility equipment from photos to pull details like serial numbers and manufacturers, helping fix missing or incomplete records.