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.
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.
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.
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.
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.
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.
An AI controller learns when a rail system’s supercapacitor should store or release electricity so trains use energy more efficiently.
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.
Software suggests what rent a landlord should charge for each apartment, sometimes updating prices often and letting managers accept recommendations automatically.
AI helps buildings run smarter by predicting repairs, reducing wasted energy, tracking sustainability metrics, and automating tenant interactions.
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 heat and power-use data from electrical systems to catch dangerous overloads before they cause outages or fires.
The system looks at rental market data and uses several prediction models together to estimate what rent a property should command.
RoofIT lets roofing contractors order materials from ABC Supply, see prices, and track deliveries without leaving the CRM they already use to run jobs.
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.
The system reads claim-related documents, looks up the right rules and references, and helps review reimbursement requests faster.
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.
AI inside Procore helps construction teams read drawings, measure spaces, summarize long documents and draft routine project paperwork.
Zendesk turns AI labels on tickets into sorting rules, queues, and dashboards so urgent or specialized cases go to the right people faster.
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.
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.
Instead of just matching ads to simple keywords, AI reads the meaning of each page so brands can place ads next to more relevant content.
A small, telecom-trained AI agent answers common customer support calls, checks live account and network systems, and either fixes the issue or hands it to a human with full context.
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.
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.
Take a trial-design AI built by regulators and adapt it with local cost and real-world healthcare data so health assessment agencies can judge how useful and cost-effective a treatment is in their own system.
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.
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.
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 turns apartment underwriting into charts and probabilities that help lenders and investors understand risk, making it easier to win approval and funding.
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.
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.
Energy prices and usage signals can change with real demand, helping providers send power where it is needed most and avoid wasteful overbuilding.
Instead of one AI per task, a larger model combines images, sensor readings, weather, and farm notes to help with many farm decisions.
By watching lots of machine health signals in one place, the factory can spot problems sooner and plan maintenance before equipment causes bigger issues.
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.
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.
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.
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.
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.
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.
A factory knowledge assistant uses retrieval-augmented generation to find the right engineering information from manufacturing documents and answer questions more accurately.
A university gave students an AI study helper they could message anytime to ask assignment questions and get guidance while preparing assessments.
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.
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 store app tells workers which jobs matter most right now, like fixing empty shelves first, so they spend less time figuring out what to do next.
The system groups customers by how they use energy and helps utilities send the right efficiency tips or programs to the right people.
AI watches how turbines, panels, and related equipment behave so operators can spot problems early and run assets more efficiently.
AI watches equipment data to spot signs of trouble early so repairs can happen before a breakdown.
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.
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.
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.
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.
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.
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.
AI reads lease documents and pulls out important details so teams do not have to manually search every page.
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.
AI keeps a property model up to date by continuously pulling new market rates, insurance information, and building data so teams can see deal impact immediately.
The tax authority uses AI to scan invoice behavior and flag companies that look fake or exist mainly to issue fraudulent invoices.
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.
Teams can explore design results for antibodies, peptides, and protein-protein interactions in example notebooks that show structures and model outputs together.
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.
Connect solar hardware to Home Assistant so it can measure how much power your panels make, show it in dashboards, and use forecasted production to trigger automations.
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.
Before AI can help, the Air Force needs a clean machine that gathers and organizes old maintenance records so analysts can test what works.
The system helps ships choose better routes and operating plans by combining vessel data, weather-aware voyage simulations, and human maritime experts, so they burn less fuel and create less CO2.
A government team uses an AI assistant called Maria to fill out and generate procurement documents that used to take specialists weeks to prepare.
A turbine’s built-in controller watches generator signals to spot early signs of faults, so operators can fix problems before the machine fails underwater.
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.
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.
This AI system uses strain data from composite airplane parts to find hidden cracks and damages that are invisible on the surface by combining smart optimization and machine learning.
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.
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.
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.
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.
A camera looks at produce on a sorting line and an AI model decides what item it is so machines can route it correctly.
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.
Software helps an uncrewed military aircraft fly and carry out missions with less direct human control.
Give the system a text recipe for a molecule, and it turns it into a machine-readable graph with useful chemistry features.
Developers can build apps that plug deeply into Seismic so teams can add custom features or connect Seismic to internal systems.
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.
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.
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.
Let homes and small producers buy and sell electricity directly, while a smart optimizer checks the local grid so trades do not overload lines or violate voltage limits.
The system looks at a help ticket and suggests which team should handle it next.
When a member contacts Modivcare, the system uses their profile and history to guide them to the right care workflow and help agents resolve issues faster.
The system offers three ways to figure out whether a participant deviated from their promised energy amount, letting operators choose between stronger privacy and lower overhead.
An AI system reads a patient description and clinical trial criteria, then finds and ranks the trials that best fit that patient.