Mentioned in 2 AI use cases across 2 industries
Use tenant preference data to recommend the right amenities and experiences—especially sustainability-focused ones—to make a building more attractive and sticky.
An AI controller learns when a rail system’s supercapacitor should store or release electricity so trains use energy more efficiently.
The system compares where trucks are going with where fuel is bought, then steers drivers to cheaper stations and flags suspicious purchases.
Zendesk turns AI labels on tickets into sorting rules, queues, and dashboards so urgent or specialized cases go to the right people faster.
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.
The system uses location data and unified records to show where unelectrified communities are, helping the government and utilities plan power-line and connection works better.
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.
AI inside Procore helps construction teams read drawings, measure spaces, summarize long documents and draft routine project paperwork.
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.
Store managers can use the same mobile system to see what shelves need attention and create tasks on the spot when they notice something missing.
AI watches equipment data to spot signs of trouble early so repairs can happen before a breakdown.
An AI controller decides in real time how much work should be done by the battery versus the supercapacitor in an electric vehicle, so the battery gets less stressed during sudden power spikes.
Use AI to decide when a supercapacitor should quickly absorb or release electricity so wind or solar power looks steadier to the 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.
An AI-like data-driven controller learns from sensor inputs and outputs to decide how a battery and supercapacitor should share work, so solar power stays smooth and the DC bus voltage stays stable even when sunlight or load changes suddenly.
Instead of using one AI for everything, investors assign different AIs to the parts they do best—research, financial modeling, and visual review—based on the property type.
AI spots tenants who may leave because of unresolved maintenance issues and helps teams fix problems fast before the tenant decides to move.
A landlord uses software to help decide whether a renter looks qualified, but must explain what the software does, test that it works, and make sure it does not unfairly disadvantage protected groups.
Instead of relying on one AI app, Linklaters is combining several AI tools so lawyers can chat, review deals, manage contracts, and use Legora together on client matters.
Use AI to predict which aircraft parts or systems may fail soon, but rank and act on those predictions using the FAA’s safety categories so the most dangerous risks get attention first.
A factory knowledge assistant uses retrieval-augmented generation to find the right engineering information from manufacturing documents and answer questions more accurately.
Comments and markups made in Bluebeam on drawings can be shown inside the submittal record so reviewers can see what was marked up, by whom, and on which page.
AI creates a first draft of a trade settlement contract using old templates plus details pulled from emails, presentations, and other documents, then turns the contract review meeting recap into a list of required updates.
Use software intelligence to decide when solar power should be sold immediately or shifted through batteries later, so the same renewable assets earn more money and operate more flexibly.
A utility can make the grid run at slightly lower voltage to save electricity, but too much rooftop solar makes voltage harder to manage. This workflow coordinates solar smart inverters with existing tap changers and capacitor banks so the utility can keep voltage in range and squeeze out more energy savings.
Give every ad creative a standard label so different TV and streaming systems can recognize the same ad and count how often people saw it.
A neural network acts like a fast traffic controller that decides, almost instantly, whether the battery or the supercapacitor should handle incoming or outgoing power in a solar-plus-storage system.
When a utility plans a job, this setup can connect the job to purchasing, inventory, accounting, and the crew that actually does the work.
AI helps buildings run smarter by predicting repairs, reducing wasted energy, tracking sustainability metrics, and automating tenant interactions.
This is like a flight recorder for medical AI: it saves what went in, what evidence was found, and how the AI answered so hospitals can inspect decisions later.
AI helps neighboring microgrids decide who should buy or sell electricity to each other and at what price, so less energy is wasted and local power is used more efficiently.
Instead of one AI per task, a larger model combines images, sensor readings, weather, and farm notes to help with many farm decisions.
The system looks at a help ticket and suggests which team should handle it next.
Engineers use AI explanations to check whether the model thinks like a real power plant should; if the explanation looks wrong, it can reveal bad sensors or missed operating problems.
Use available mould stock by date/code to decide when and how much same-grade liquid metal to melt, instead of planning melts in isolation.
LeddarTech replaced scattered Word and Excel files with one system that tracks product requirements, tests, and changes for LiDAR used in autonomous vehicles, making safety audits and teamwork much easier.
Use AI to gather the right maps, plans, monitoring records, and maintenance evidence into one closure package so a mine can show how it is managing a final void.
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.
Use machine learning to tell smart power inverters how to behave so the local grid stays stable and efficient as conditions change.
The system gathers what customers want and what regulators require, then makes sure the quality system is built to meet those needs.
Connects utility asset program data to analytics, field work, and customer systems so teams can monitor programs, act on issues, and share information across departments.
Instead of AI only helping write code, teams use AI helpers for reviews, tests, security fixes, deployments, and even incident response. Humans set the rules, and the AI handles repetitive coordination work.
When an employee asks IT for help, the system reads the request, checks whether the person is allowed to make it, looks up the right knowledge, figures out what the issue is, and sends the ticket to the right team automatically.
AI reads lease documents and pulls out important details so teams do not have to manually search every page.
An AI controller decides when a battery should provide energy and when an ultracapacitor should handle fast power bursts, so the system uses each device for what it does best.
A built-in AI helper answers questions instantly for staff, tenants, guests, or students, and automates repetitive building tasks so support teams do less manual work.
Helps trial teams see how many people are joining a study, how fast enrollment is happening, and whether they are on track versus plan.
Engineers ask the AI to walk through different quality decision paths so they can see what might happen before choosing an action.
M&T's developers use AI inside GitLab to help write code faster, but engineers still review and finish the work.
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.
Software now helps Pluxee automatically review interactions, forecast staffing needs, and track coaching, instead of relying on spreadsheets and manual checks.
An AI system watches building sensor data, maintenance history, and resident feedback to help property managers decide what to fix, when to allocate staff, and how to improve tenant experience.
A smart valve automatically adjusts how much water flows through pipes so pressure stays stable and pipes are less likely to burst or leak.
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.
Use software to decide when water treatment equipment should run so the grid stays balanced while water service is still delivered.
AI keeps air pressure steadier for production lines like bottling, so machines run more smoothly and output improves.
AI acts like a smart conductor for buildings and electric vehicle fleets, deciding when to charge, store, or use energy so sites save money, stay comfortable or operational, and help the grid at the same time.
A software system helps utilities keep track of important equipment and infrastructure, like a smart filing cabinet and workflow hub for physical assets.
Instead of just using valves to lower water pressure, a utility can use smart selection software to find where replacing those valves with power-generating devices makes financial sense.
When a worker logs into a station and picks a job, the system checks their HR skill profile to make sure they’re approved for that exact task.
An AI reviews a draft contract against a company’s lawyer-written rulebook, highlights unusual or missing terms, and gives an early risk read before a human negotiates it.
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.
A property company uses an always-on chatbot to answer renter questions and collect new prospect details even when staff are offline.
An optimization system lets neighboring microgrids buy and sell electricity directly with each other while checking that the local power network is not overloaded.
The same AI-enabled service platform used by IT is extended to other internal teams so employees get help through one shared system.
A single model can look at words, pictures, sounds, and videos together so companies can understand richer customer content in one system.
AI can help with school tasks, but people should ask the questions first and make the final decisions after thinking about the results.
The system creates analytics snapshots of meter data validation and estimation exceptions so teams can track data quality problems in one place.
Like a smart assistant that gathers all the important building paperwork from different folders and turns it into one final handoff package for the owner.
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.
A mobile app uses AI to look at equipment photos in the field, point out possible problems, and help workers record what they found correctly.
The company built one cloud analytics hub so teams can pull together outage and operations data, analyze it faster, and use past events to make better future decisions.
A utility replaced disconnected old systems with an integrated IBM Maximo setup so teams can manage assets, maintenance, and operations in one digital environment instead of by hand.
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.
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.
Apps are using very short missed calls instead of text messages to verify users. An AI system watches network traffic, spots these fake-looking verification calls, and helps the telco stop losing money from them.
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.
The bank uses AI and rules to check each payment in milliseconds and decide whether to allow it, block it, or ask the customer to confirm it.
Use AI to predict where utilities should spend money first on grid growth, reliability improvements, and old equipment replacement over the 2025-2029 cycle.
A script can open a new support ticket in Zendesk automatically instead of someone creating it by hand.
An AI system helps aircraft designers quickly find the right information and past examples to design tools for assembling airplane wings, making their work faster and more accurate.