General Electric Company (GE) is a global industrial technology company focused on aerospace, power, and renewable energy. Following a multi‑year restructuring, GE is transitioning into separate public companies, with GE Aerospace and GE Vernova as its primary businesses. The company develops advanced hardware and software solutions that power aircraft, energy infrastructure, and industrial systems worldwide.
Chip factories can use special patterning and stacking methods to build tiny supercapacitors right into the chip during manufacturing.
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.
Investors can estimate how much more money a building could make if AI helps more renters renew, then use that estimate when deciding what to pay for the property.
The same AI helper can answer residents’ common questions and remind them about renewing their lease, making living at the property feel easier and more responsive.
A landlord uses tenant surveys to improve retention predictions, but adjusts for the fact that some groups answer surveys more than others so the model does not unfairly favor louder voices.
IAS uses contextual signals to steer ad buying toward better-performing pages, and brands then measure stronger click-through, conversion cost, or return on ad spend.
The system looks at rental market data and uses several prediction models together to estimate what rent a property should command.
When the sales agent is connected to Salesforce, admins can grant it extra permissions so it can read activities, tasks, events, and custom fields needed to fully research leads and optionally write summaries back.
AI would eventually handle some maintenance-related steps automatically in the background so workers do less repetitive system work.
The system compares where trucks are going with where fuel is bought, then steers drivers to cheaper stations and flags suspicious purchases.
An AI agent checks invoices against contracts and service expectations, spots anomalies, and drafts variance commentary so asset managers can protect NOI.
Zendesk turns AI labels on tickets into sorting rules, queues, and dashboards so urgent or specialized cases go to the right people faster.
A university gave students an AI study helper they could message anytime to ask assignment questions and get guidance while preparing assessments.
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.
Instead of different departments working separately, WIN Garment uses one shared digital workspace so designers, buyers, technicians and sales can work together online from anywhere.
Teams can preview how personalization changes rankings for a specific shopper and query before turning it on for everyone.
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.
As a person clicks around right now, the system updates what it thinks they want and reorders recommendations on the fly.
AI watches heat and power-use data from electrical systems to catch dangerous overloads before they cause outages or fires.
A camera looks at produce on a sorting line and an AI model decides what item it is so machines can route it correctly.
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 agent reads tenant messages from email, chat, and forms, figures out whether people are happy or upset, spots urgent problems, and gives managers a daily summary of what needs attention.
RoofIT lets roofing contractors order materials from ABC Supply, see prices, and track deliveries without leaving the CRM they already use to run jobs.
AI inside Procore helps construction teams read drawings, measure spaces, summarize long documents and draft routine project paperwork.
This workflow teaches an AI to understand whether Chinese housing-related social posts are upbeat, neutral, or worried, so analysts can measure market mood instead of reading millions of posts by hand.
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.
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.
The company built a dashboard that connects each lease to its rent changes over time, so leaders can see which tenants renewed, how much rents increased, and which properties or teams are performing well without manually stitching spreadsheets together.
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.
Software suggests what rent a landlord should charge for each apartment, sometimes updating prices often and letting managers accept recommendations automatically.
Use past buoy measurements and weather-related signals to predict near-future wave height at offshore wind sites, helping crews and operators decide when it is safe and efficient to work at sea.
The system reads claim-related documents, looks up the right rules and references, and helps review reimbursement requests faster.
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 turns apartment underwriting into charts and probabilities that help lenders and investors understand risk, making it easier to win approval and funding.
AI spots tenants who may leave because of unresolved maintenance issues and helps teams fix problems fast before the tenant decides to move.
An AI system is being designed to predict droughts, floods, and other severe weather in Brazil much earlier, helping the country prepare before damage happens.
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.
The AI predicts which paying players are likely to quit at a certain level, so the game can help them with boosts or tips before they give up.
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.
The system watches trucks in real time and alerts the team if a driver goes off route, stops unexpectedly, or is running late so they can fix problems fast.
Give the system a text recipe for a molecule, and it turns it into a machine-readable graph with useful chemistry features.
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.
The software looks at property data, predicts what might happen next and suggests actions to help owners lower costs, reduce risk and make more money.
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.
An AI assistant for manufacturing that can read mixed document types—written explanations, diagrams, equations, and tables—and answer questions more accurately by looking up the right evidence first.
After people moved in, the team watched how the building behaved, listened to complaints, found a hidden heating problem, and adjusted controls to fix it.
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.
A digital copy of the aircraft’s battery and power system uses physics plus AI to track wear and predict what will happen next.
The system looks at customer history and current behavior to spot who may leave soon, explains why, and can automatically trigger actions to keep them.
Combine crop data from many countries to estimate the world's wheat supply and how much will remain in storage.
A drone flies over cocoa and cashew farms at different growth stages, and an AI system combines the images with tabular farm data to estimate crop condition and likely yield.
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.
The AI learns that in calm markets sustainability scores matter more, but in stressful markets news mood matters more, helping portfolio managers shift what they trust.
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.
When too much rooftop or feeder solar pushes voltage too high, the utility can tell many solar inverters to absorb just enough reactive power together so the grid stays safe without turning solar output down.
An AI assistant helps fleets and drivers answer electronic logging device questions for cross-border trips using the specific FMCSA cross-border FAQ material instead of guessing from U.S.-only summaries.
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.
Teams can explore design results for antibodies, peptides, and protein-protein interactions in example notebooks that show structures and model outputs together.
AI helps buildings run smarter by predicting repairs, reducing wasted energy, tracking sustainability metrics, and automating tenant interactions.
For storage chips, the safety system can only hold one error at a time, so if several problems happen together some may be lost and software should assume the worst.
The company uses AI to spot which tenants are likely to not renew their leases, so property teams can step in early and try to keep them.
Before AI can help, the Air Force needs a clean machine that gathers and organizes old maintenance records so analysts can test what works.
A government team uses an AI assistant called Maria to fill out and generate procurement documents that used to take specialists weeks to prepare.
It helps ships choose the best path by looking at weather, waves, and water depth so they burn less fuel.
A retailer turns personalization on in platform settings instead of changing app code every time, making it easier to test whether personalized search performs better.
A camera takes pictures of harvested crops, and an AI system sorts them into quality grades the way an experienced inspector would, but faster and more consistently.
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.
An online prescription eyewear retailer uses an AI system that learns from shopper behavior to suggest products each person is more likely to want.
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.
Energy prices and usage signals can change with real demand, helping providers send power where it is needed most and avoid wasteful overbuilding.
One small AI first decides what kind of help request came in, then sends it to the right expert AI—or to two expert AIs at once if both are useful.
By watching lots of machine health signals in one place, the factory can spot problems sooner and plan maintenance before equipment causes bigger issues.
Instead of one AI per task, a larger model combines images, sensor readings, weather, and farm notes to help with many farm decisions.
The AI spots tiny warning signs in how a truck runs—like heat, vibration, or braking patterns—so the team can replace a failing part before it causes a major breakdown.
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.
Software helps an uncrewed military aircraft fly and carry out missions with less direct human control.
Developers can build apps that plug deeply into Seismic so teams can add custom features or connect Seismic to internal systems.
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.
Instead of waiting through a long paper-heavy process, some water-use permits are intended to be issued instantly in a fully digital flow.
The tool studies which kinds of contacts became qualified leads before and then scores new contacts based on how similar they are to those successful contacts.
Use an AI platform to check whether genes and proteins affected by a drug also appear abnormal in disease datasets, helping confirm the drug is acting on biology that matters.
An AI system reads a patient description and clinical trial criteria, then finds and ranks the trials that best fit that patient.
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.
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.
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.
Doctors do not hand control to the AI; they choose what data the system uses and set safe operating limits, while the AI helps suggest doses during treatment.
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.
Sensors watch how an old mine tunnel bends and strains while heavy ore is piled above it, and software uses that live evidence to decide whether the tunnel can safely handle more load.