EY (Ernst & Young Global Limited) is one of the world’s largest professional services organizations, providing assurance, tax, consulting, and strategy and transactions services. Operating as a global network of member firms in over 150 countries, EY serves corporations, governments, and startups across most major industries. The firm is increasingly focused on technology-enabled transformation, including data, analytics, and AI-driven solutions.
A hospital system used software that helps doctors choose the right tests, treatments and care setting so patients get appropriate care without extra hospital days or avoidable services.
This AI system uses data from airplane flights to create a digital copy (digital twin) of key airplane parts, predicting how much life those parts have left and helping plan maintenance and flight schedules smarter.
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.
AI systems watch over airplane parts to spot damage early, keeping flights safe and saving money on repairs.
AI systems predict when airplane parts might fail so they can be fixed before breaking.
Using AI to predict when an airplane needs maintenance so it can be fixed just in time, saving money and keeping planes flying longer.
Using smart computer programs to watch and check airplane parts for damage or wear so they can be fixed before problems happen.
A camera-and-AI machine watches tomatoes on a conveyor, spots bad ones, and kicks only those out so more good tomatoes are kept.
Aegon uses software that automatically checks whether its business systems and screens still work correctly after changes, instead of relying heavily on people to test everything by hand.
Think of this as putting a smart assistant behind every player, coach, and team executive. It watches every game, every training session, every fan interaction, and then suggests what to do next to play better, avoid injuries, and grow revenues.
This is a playbook for getting buildings and facilities ready to actually use AI – like teaching a building to ‘talk’ clearly about its energy use, maintenance needs, and occupancy so that AI tools can make smart decisions instead of guessing.
This is like giving oil and gas equipment a digital “check‑engine light” that predicts problems before they happen. It watches sensor readings, work orders, and maintenance history and then tells you which assets are likely to fail and when, so you can fix them in a planned shutdown instead of during a costly emergency.
Imagine your entire oil and gas operation—wells, pipelines, refineries—covered in smart sensors and watched by an always‑awake digital control room. That digital brain constantly learns from data, spots problems before they happen, and quietly adjusts valves, pumps, and schedules so you produce more oil and gas with less downtime, waste, and risk.
This is like giving a bank’s fraud and compliance team a super-smart assistant that watches every transaction in real time, learns what “normal” looks like for each customer, and then flags only the truly suspicious ones for humans to review.
This is about using AI as a super-smart control center for factories and supply chains. It watches machines, inventory, orders, and logistics in real time, then predicts problems before they happen and suggests the best way to run production so you waste less time, material, and money.
This is about using AI as a smart junior assistant for lawyers — helping read huge piles of documents, draft routine language, and surface relevant cases so the attorney can focus on judgment and strategy.
Think of a data center as a giant, always‑on factory plugged into the power grid. Gridmatic builds an AI "power manager" that constantly watches electricity prices, grid conditions, and the data center’s workload, then turns dials up or down so the facility uses cheaper, cleaner power without sacrificing reliability.
This is like using extremely smart microscopes and calculators on a computer to design new medicines before you ever mix chemicals in a lab. The software predicts which molecules are most likely to work, so scientists test 100 promising ideas instead of 10,000 random ones.
This is like giving airline pilots a smart co-pilot that never gets tired: an onboard AI that continuously watches the flight situation, predicts what might happen next, and suggests or executes helpful actions while keeping the human pilot in charge.
This is like giving your supply chain a smart, always‑on co‑pilot that can read all your plans, emails, contracts and forecasts, then suggest better decisions — from what to buy, where to make it, and how to ship it — in plain language.
This is like putting smart ears and eyes on your machines so they can tell you when something sounds or looks wrong—before it breaks. Small sensor boxes sit on the equipment, watch and listen in real time, and warn you early so you can fix problems during planned downtime instead of after a costly failure.
This is about using AI as a super-fast paralegal and forensic analyst that can read millions of documents, emails, and records, spot patterns, and summarize findings to support disputes, investigations, and regulatory responses—while staying within new legal and compliance rules.
This is like giving a commercial building’s heating and cooling system a smart autopilot. It watches how energy is used, learns building patterns (people coming and going, outside weather, peak loads), and automatically tunes HVAC settings to keep tenants comfortable while using less electricity.
Think of Cohesion as a digital command center for large office or mixed‑use buildings. It connects elevators, HVAC, security, access control, and occupancy data into one intelligent system so building operators can see what’s happening in real time and let software make many of the small adjustments people used to make manually.
Think of a large office building as a living body. In the past, the heating, cooling and lighting were like organs running on fixed schedules, whether people were there or not. AI turns the building into a “smart body” that can sense where people actually are, how hot or cold it is, what energy costs right now, and then automatically adjusts everything in real time to stay comfortable while using far less energy.
This is like a standardized exam for AI lawyers: a big, rigorous test to see how well AI systems actually understand and analyze contracts in realistic legal scenarios.
Think of this as Netflix building its own very smart "taste brain" that understands movies, shows, images, and text, then wiring that brain into all the ways it personalizes what you see — rows, artwork, search, and more — instead of relying on a bunch of separate smaller brains.
This is like giving Netflix a smart brain that quietly watches what you watch, when you stop, what you search for, and then rearranges the entire app, recommendations, images, and streaming quality just for you—millions of people at once, all differently.
This is a study that asks: "How much value do Netflix-style ‘Because you watched…’ recommendations really create?" It measures what happens to user behavior and business outcomes when you turn personalized recommendations on vs. off.
This is Netflix’s “smart brain” that watches what every viewer clicks, skips, and binges, then uses a giant AI model to decide which shows and movies to put in front of each person so they’re more likely to hit play.
Think of Luminance as a super-fast junior lawyer that can read huge piles of contracts, highlight key clauses, and answer questions about them in plain English, but always within law-firm standards for accuracy and control.
This is Netflix’s R&D lab for making sure every member quickly finds something they’ll love to watch. Think of it as a constantly learning concierge that rearranges the entire Netflix store for each viewer, in real time.
Think of this as giving every lawyer a super-smart digital paralegal that can read huge volumes of cases, laws, and documents in seconds, suggest arguments, and draft materials—while the human lawyer still makes the final calls and ensures ethics and accuracy.
This is like giving lawyers a super-fast, very careful junior associate who can read long contracts in seconds, suggest edits, draft new clauses, and flag risks, but always under the lawyer’s supervision.
Think of Draftwise as a “supercharged legal autocomplete” that lets lawyers draft contracts and documents using the firm’s best past work and clauses, suggested instantly as they type.
This is like giving every lawyer a super-fast, ultra-careful digital paralegal that reads contracts, finds definitions and references, and checks for problems in seconds instead of hours.
This is like a smart air-traffic controller for a factory: it looks at all your orders, raw materials, machines, and people, then constantly rearranges the schedule so everything runs smoothly, on time, and at the lowest cost.
This is like a weather forecast, but for how much energy a building will use. It learns from past data about the building (design, materials, historical meter readings, weather) and then predicts future consumption so you can plan and optimize better.
This is like giving a commercial building a smart autopilot that constantly watches how it uses heating, cooling, and energy and then quietly adjusts everything to be cheaper, more reliable, and more comfortable for occupants.
Imagine a super-detailed digital twin of an old timber building that can almost build itself: you feed it survey data and drawings, and an AI-driven system assembles a smart 3D model that knows what each beam and joint is, how it fits together, and how the building has changed over time.
Think of this as a very smart data detective for energy and mining companies: it combs through mountains of operational, geological, and financial data to spot hidden patterns that humans miss, then suggests where to dig, how to run equipment, and where money is being wasted.
Imagine every time you open your TV, there’s a smart concierge who has watched everything you’ve ever seen, remembers what you liked, what you quit after 5 minutes, what you binged in a weekend, and what people like you enjoy. That concierge quietly rearranges the shelves so the things you’re most likely to love are always right in front of you. That’s what a Netflix-style recommender system does—at software scale for millions of viewers.
Think of this as putting a “smart brain” on top of every critical piece of oil & gas equipment. It constantly listens to sensors, learns what ‘normal’ looks like, and warns you before something breaks so you can fix it at the best possible time.
This is like putting a smart ‘check-engine’ light on every critical asset in an oil & gas operation. Instead of waiting for something to break, software constantly watches sensor data and warns you in advance when a pump, compressor, or pipeline component is likely to fail, so you can fix it during planned downtime.
This is like a smart mechanic for power-plant valve actuators: it watches sensor data, predicts when parts are likely to fail, and also explains in plain engineering terms why it thinks a failure is coming (e.g., which pressures, temperatures, or vibrations are driving the risk).
This is like giving every lawyer a super-fast digital assistant that can read huge piles of contracts, flag issues, and summarise key points in minutes instead of hours—while the human lawyer still makes the final calls.
Think of the future transport system as a giant, city-wide brain. Instead of each car, bus, or train acting on its own, AI watches traffic, weather, demand, and incidents in real time and then orchestrates everything—routes, signals, pricing, and even maintenance—so people and goods move faster, safer, and cheaper.
This is a strategy and analytics approach that helps large consumer packaged goods (CPG) companies use their data and AI as a new kind of ‘economies of scale’—not just buying more shelf space or running bigger TV campaigns, but spotting profit opportunities and efficiency gains across brands, markets, and channels using advanced analytics and generative AI.
Think of this as using a very fast, very smart legal intern that can read huge amounts of text, find relevant information, and draft first versions of documents—but still needs a real lawyer to check, interpret, and sign off.
This is about using AI as a smart legal assistant for law firms—helping read and draft documents, search case law faster, and automate routine legal tasks so lawyers can focus on strategy and clients.
This is like giving your building’s heating and cooling system a smart autopilot. It watches how your building behaves, learns patterns of occupancy and weather, and then constantly tweaks HVAC settings to keep people comfortable while cutting energy waste and emissions.
Think of a bond trader trying to place orders in a busy marketplace. The trader wants to know: “If I shout this price, what are the chances someone actually trades with me soon?” This research is about building smarter calculators that predict how likely a bond order is to get filled, and how fast, so trading algorithms can choose better prices and order types automatically.
Think of a city where every bus, traffic light, and parking space can talk to each other in real time, and an AI ‘traffic conductor’ continuously listens and adjusts things so people and goods move faster and more safely with less waste.
This is like a very smart mechanic for jet engines that continuously listens to many different sensors and, using patterns learned from past engines, estimates how much life is left before something needs repair or replacement.
Think of this as a smart co-pilot for buildings: it watches how your facilities are used, how equipment behaves, and what work orders come in, then suggests what to fix first, when to schedule maintenance, and how to run the building cheaper and smoother.
Like having a junior contract lawyer on call 24/7 who can read your contract, highlight risky clauses, and explain them in plain English before you sign.
Legora is very likely an AI assistant focused on legal work—think of it as “ChatGPT that’s tailored for lawyers and legal documents,” helping review, search, and draft legal materials faster and with fewer errors.
Think of Intellosync AI as a legal assistant that lives inside your Microsoft 365 tools (like Word/Outlook) and helps you read, draft, and summarize legal documents faster and more accurately.
This is like having a tireless junior lawyer who can quickly read, draft, and explain legal documents, but works inside your computer instead of at a desk.
This is like giving a retailer a very smart crystal ball that predicts how much of every product customers will buy, and then automatically adjusts orders and inventory so shelves are full but storerooms aren’t overflowing.
This is about how rich investors are using smarter trading technology and AI tools—like ultra-fast, data‑driven autopilots—to manage and grow their money instead of relying only on human advisers and manual trades.
Think of a smart building as a self-driving car for energy and operations: sensors constantly watch what’s happening (people, temperature, light, equipment), and AI decides when to heat, cool, light, or ventilate each space so you use the least energy without sacrificing comfort.
Imagine a smart legal assistant that reads large volumes of laws, contracts, and case documents and automatically pulls out the important facts, clauses, and legal concepts so lawyers don’t have to search manually.
Think of this as a building’s "autopilot for energy": it constantly watches how the building is being used, how hot or cold it is, what the weather and prices look like, and then automatically adjusts heating, cooling, lighting and other systems to keep people comfortable while using as little energy (and money) as possible.
This is like a smart mood board generator for interiors: you describe the room and style you want, and the AI instantly shows you many different design ideas and looks you can explore or refine.
This is like having an AI engineer that automatically rearranges how equipment or components are laid out in an energy system to squeeze out more performance and lower costs.
This is like having a super-smart assistant inside your building design software that automatically spots and fixes piping and wiring conflicts before anyone steps on site.
Like giving your mechanical, electrical, and plumbing (MEP) design team a tireless junior engineer that can quickly test many design options, spot clashes, and optimize layouts before anyone starts building.
This is about how Netflix-style “Because you watched…” lists are created. The system watches what you watch, when you stop, what you rewatch, and then predicts what you’re most likely to enjoy next—like a super‑attentive video store clerk who’s seen your entire viewing history.
This is like giving your thermal energy storage system a smart brain that can learn how it behaves, suggest better designs, and continuously fine‑tune how it runs to save energy and money.