Mentioned in 1 AI use cases across 1 industries
AI helps buildings run smarter by predicting repairs, reducing wasted energy, tracking sustainability metrics, and automating tenant interactions.
Compare different apartment layout types created from old buildings and rank which ones tenants prefer before scaling a conversion approach.
An algorithm decides in real time when a UPS should draw fast burst power from an ultracapacitor versus steadier energy from a battery, so backup power stays stable and the battery is stressed less.
An AI-assisted control system checks whether what an energy company promised in contracts, measured in meters, priced in rating engines, billed on invoices, taxed, collected, and recognized as revenue all match, so money does not slip through the cracks.
A public library of ready-made automation recipes helps people find and reuse AI-enabled workflows instead of building them from scratch.
An AI controller learns when a rail system’s supercapacitor should store or release electricity so trains use energy more efficiently.
The team used software to test many possible village types and electricity needs so they could plan what future microgrids might cost and how big they should be.
Once the utility network is built correctly, teams can ask the system to follow connections and show what equipment belongs to which part of the grid.
Energy prices and usage signals can change with real demand, helping providers send power where it is needed most and avoid wasteful overbuilding.
Use AI trained on many past trials to test how design choices—like endpoints or protocol details—might affect the odds of success before running the study.
Use AI-style clustering and simulation to test many wave farm designs, then pick the setup that makes the most electricity while also reducing wave impact near shore.
Santee Cooper gives customers a prepaid electricity balance and helps them see usage sooner so they can change behavior before bills get too high.
The utility used AI to watch hundreds of thousands of smart meters, spot missing or suspicious readings, and send teams to fix leaks, backflows, and unmapped consuming meters before revenue is lost.
The mine uses many sensors to watch whether pit walls are starting to move, sends that data to the cloud, predicts what will happen next, and warns staff before a dangerous slope failure occurs.
Instead of waiting until money is already lost, AI looks at past patterns and warns teams where future billing or settlement problems are most likely to happen so they can check those areas first.
The platform looks through huge amounts of smart meter data to spot leaks, backflows, or suspicious patterns so utilities can stop losing money and respond faster.
Use recent wave measurements to predict the next few moments of ocean motion so a wave energy machine can adjust itself in time to capture more power safely.
Instead of just showing raw numbers, the team looks for patterns over time and explains what they learned, what changed, and what they will optimize next.
Before installing power systems in remote villages, planners can simulate different microgrid setups to choose what will work best.
Instead of clicking around a map, analysts can pull wave data directly into code and automate studies of how devices might perform at many sites.
It gives teams a disciplined way to check whether their marketing measurement model makes sensible cause-and-effect assumptions before trusting the numbers.
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.
An AI system helps planners figure out how to expand a village’s solar or off-grid power system as electricity needs grow, while reusing existing equipment and comparing upgrade options.
Give the system a text recipe for a molecule, and it turns it into a machine-readable graph with useful chemistry features.
Instead of billing customers from separate spreadsheets and systems, one setup connects contracts, installed equipment, meter readings, and finance so bills are created automatically and correctly.
A utility takes its old network data, matches each asset to the right standard bucket in Esri’s Utility Network Foundation, and loads it into ArcGIS in several passes so the new system works correctly.
When new work orders keep showing up during the day, this workflow simulates the factory and uses scheduling logic to keep updating the plan.
An AI assistant tests many early building design options and shows architects which ones best balance energy use and carbon impact before major decisions are locked in.
The utility used SEW’s digital platform to sign up households for an emergency energy-saving program, send them communications, and help them reduce electricity use when the grid is stressed.
Shows which service agreements have gone unbilled, how long they have been waiting, and which accounts have the biggest billing delays.
The system groups customers by how they use energy and helps utilities send the right efficiency tips or programs to the right people.
PSEG deployed a new outage management system that gives staff near real-time information so they can decide faster where crews should go and restore power sooner.
A chat assistant is added around Maximo so workers can ask plain-language questions about maintenance and asset management and get useful answers.
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.
Money-related data from the utility billing system is automatically sent to finance systems so accounting records stay up to date.
The hotel system suggests the best extra things to offer each guest—like room upgrades or amenities—at the right moment, so staff can ask naturally and earn more revenue.
Use planning analysis to decide where solar mini-grids make more sense than extending the main power grid.
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.
After checking child safety reports for Lialda, FDA uses the findings to decide whether the medicine’s warning label needs new side effects added or whether routine monitoring is enough.
Use AI to combine different power sources and grid options so data centres can get reliable electricity all day while still pursuing clean-energy targets.
Cameras and code readers automatically check tiny markings and defects on pump parts so bad parts are caught almost every time, while each part gets a digital history.
Feed in how sand-filled saltwater hits a turbine blade and what the blade surface looks like, then estimate how badly the blade is eroding and where damage is likely to worsen.
Instead of waiting through a long paper-heavy process, some water-use permits are intended to be issued instantly in a fully digital flow.
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.
The app reads claim paperwork like a smart assistant, pulls out important facts, and helps adjusters make faster decisions.
Ameren and SAS used smart meter data to infer when neighborhood transformers are overloaded, failing, or causing outages, so crews can fix problems earlier without installing expensive sensors on every small transformer.
The system not only estimates a home's value, it also shows which traits like location or size matter most for the price.
Use AI to balance many sustainability goals at once—water, energy, certification, affordability, public benefits, and historic preservation—so the project team can choose the best overall design package.
After a customer call ends, AI writes the notes and summary for the agent so they spend less time on paperwork.
The system notices what a guest might need, like a baby cot or late checkout, and automatically creates the right tasks so staff can deliver it on time.
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.
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.
The platform studies customer usage and account data so energy retailers can tailor prices and offers to what each customer actually needs.
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.
The platform helps create lots of skincare videos that still feel like real people sharing honest experiences, not robotic ads.
The hotel automatically sends guests timely texts and emails offering upgrades and dining options, making it easier for guests to buy extras and for staff to do less manual selling.
Tenova installed a large solar plant at its Castellanza site to make part of its own electricity instead of buying it all from the grid.
The utility used SEW’s SmartWX platform to make sure field crews get the right job orders and information faster, so they can fix issues sooner and waste less time.
Utilities connect their maps, work orders, and asset databases so everyone sees the same asset details and discrepancies can be found during inspections.
An energy company and university used a planning workflow to decide where EV chargers should go, how many are needed, and whether each site should get slow or fast chargers based on how long people usually stay there.
The platform helps utilities set up complicated rate plans faster and test them safely before using them on real customer bills.
AI is used to study where EV drivers are likely to need charging in a city and then recommend the best places to build fast chargers so they are useful and not wasted.
The AI spots suspicious hospital purchase bids, then auditors verify the warning and stop or fix the purchase before the government overpays.
Oracle provides downloadable integration guides so utility teams can see how different cloud systems connect before they deploy or upgrade them.
Instead of using every old battery equally, AI decides in real time which battery module should work harder and which should rest, so the whole system lasts longer and delivers more usable energy.
Instead of waiting to fine companies, the tax authority automatically spots filing mistakes and warns businesses so they can fix many issues themselves before penalties happen.
The power company upgraded its maintenance and service system so teams handling wires, meters, and field work can work faster together and serve customers better.
An energy utility can pull outage notices from another outage system into a customer-service portal so agents can quickly look up what happened and which customers are affected.
Use AI to sort outage events into the right categories and help prepare reliability reports regulators expect.
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.
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.
Use AI to combine field, technical, and community data so planners can figure out the best way to bring electricity to hard-to-reach Amazon communities without ignoring local realities.
Use AI to predict where utilities should spend money first on grid growth, reliability improvements, and old equipment replacement over the 2025-2029 cycle.
It acts like a shared brain for utility data, connecting analytics with billing, customer, meter, asset, and other Oracle utility systems.
A manufacturer tells regulators in advance what AI software updates it expects to make, how it will test them, and how it will keep the device safe after release.
The framework gives policymakers a menu of good waste-management options showing how money, emissions, and climate-related social costs trade off, so they can choose what best fits their goals.
AI systems analyze various aerospace and defense data to detect and predict threats in real time, helping decision-makers respond faster and more accurately.
This system uses AI to watch aircraft parts and batteries in real time to predict when they might fail or get damaged, so maintenance can happen before problems occur.