Mentioned in 131 AI use cases across 21 industries
The software gives nurses structured suggestions and reminders for planning care and handling issues like infections or wounds.
The system groups customers by how they use energy and helps utilities send the right efficiency tips or programs to the right people.
This is like a super-powered hiring and talent map for your company: it scans millions of profiles and your internal data to suggest the best people to hire, promote, or reskill, instead of relying on manual resume review and gut feel.
Imagine giving your fraud investigators a tireless digital assistant that reads billions of transactions, emails, and claims every day, flags anything that “looks off,” and explains why it’s suspicious so humans can step in before the money is gone.
This is like an early-warning radar for HR: it looks at patterns in employee data (tenure, performance, pay, engagement, etc.) and flags which people are most likely to quit soon so managers can step in before it happens.
Think of this as a smart HR analyst that reads lots of employee and HR data (and sometimes documents) and then suggests who to hire, how to develop people, or where risks are – faster and more systematically than a human team could do manually.
This is like giving your HR team a smart telescope that looks inside your existing workforce to spot hidden skills, future leaders, and internal candidates for open roles, instead of always looking outside for new hires.
Imagine your recruiting team got a super-fast, tireless assistant who can read every resume, screen every candidate, and flag the best matches 24/7, while also learning from 20 years of what has and hasn’t worked in hiring.
Think of this as an HR co-pilot: a smart assistant that reads policies, resumes, and HR data and then suggests actions or answers questions for HR teams and managers.
Imagine a hotel that remembers every guest like a great concierge: what room temperature they like, which pillow they prefer, when they usually arrive, and what they tend to order. AI in hospitality is the digital brain behind that experience—quietly watching patterns in bookings, reviews, and operations so staff can serve guests faster, more personally, and with fewer mistakes.
This is about using AI as a smart assistant for hiring and HR: it helps you sift through piles of resumes, screen candidates, and manage communication so your team can focus on interviewing and making better hiring decisions.
This is a smart “auto‑pilot” for hotel room pricing that constantly looks at demand, bookings, and market conditions, then suggests or applies the best room rates across the My Place Hotels chain.
This is like having a very smart auditor that continuously watches tax records, bank-like transaction trails, and filing patterns to spot who might be under-reporting income or committing tax fraud, and then alerts tax officers to investigate those specific cases first.
Think of this as a smart engine inside an online store that automatically shows each shopper the most relevant products, content, and offers, based on everything SAP already knows about them and similar customers.
This is like giving your marketing team a crystal ball that looks at all the clicks, calls, and purchases your customers made in the past and then guesses what they’re likely to do next, so you can talk to the right people with the right offer at the right time.
Imagine your retail planning team with a super-analyst who has read every sales report, every inventory file, and every marketing plan you’ve ever had, and can instantly tell you what to buy, how much, where to send it, and when to mark it down. That’s what AI-powered retail planning tools like Toolio aim to do across the full planning calendar.
Think of this as a very fast, very picky auditor that looks at every transaction and customer pattern 24/7 and flags only the truly suspicious ones, instead of drowning your compliance team in false alarms.
This is like giving pharma companies a super-fast, tireless analyst that can help design, run, and monitor drug trials more efficiently by spotting patterns in patient data and documents that humans would miss or take months to find.
This is like giving your online merchandising team a super-smart assistant that constantly watches sales, inventory, and trends, then tells you what to stock, when to reorder, and how to price and present products for maximum profit across the whole product lifecycle.
This is like giving your drug development teams a super-fast assistant that can read all past trial data, spot patterns humans miss, and help design and run smarter clinical trials.
Think of clinical trials as a long, expensive treasure hunt to find out if a new drug really works. This paper describes how AI can act like a super-smart assistant at every step—finding the right patients faster, spotting hidden safety signals earlier, and predicting which trials are most likely to succeed—so you spend less time and money to reach the answer.
This is like a smart, interactive map of your entire organization that lets HR and business leaders test different org structures and workforce plans before making real-world changes, using AI to highlight risks, gaps, and cost impacts.
This is like having a smart digital salesperson for every single shopper that instantly figures out what offer or promotion will convince them to buy right now—based on what they’re doing, what they’ve bought before, and what similar people responded to in the past.
Think of this as a smarter CRM that not only stores customer details but also watches what your customers do, predicts what they’re likely to want next, and nudges your sales and service teams with “do this now” suggestions.
This is like a smart early‑warning system for phone and internet companies: it watches customer behavior, predicts who is likely to cancel soon, and automatically suggests (or triggers) the right offer or outreach to keep them from leaving.
Imagine every recruiter has a super-smart digital assistant that never sleeps, scans thousands of resumes in minutes, talks to candidates, and keeps hiring managers updated automatically. That’s what AI recruiting agents do for the hiring process.
Think of Salesforce as a digital command center where all your customer information, sales activities, and marketing efforts live in one place — and now it has an AI copilot that recommends who to call next, what to say, and automates a lot of the busywork.
This is like giving every B2B salesperson a smart digital co-pilot that watches all your customer data (emails, CRM, website visits, purchase history), predicts which deals are most likely to close, recommends the next best action, and drafts the right message to send at the right time.
This is like giving a CPG company a super-analyst that never sleeps: it scans all your sales, pricing, promotions, store, and external data to automatically surface why performance changes, where growth is hiding, and what to do next.
Imagine your logistics network as a huge, busy train station where trains, trucks, and packages are constantly in motion. AI acts like a super-dispatcher watching everything in real time, predicting delays, and rerouting shipments so parcels still arrive on time at the lowest possible cost.
Think of it as a super-planner that never sleeps: it constantly looks at orders, machines, materials, and workers, then automatically updates your production schedule, flags problems, and suggests fixes instead of waiting for humans to rebuild the plan in Excel.
This is like giving your factory’s online supply chain a smart GPS and weather system: it constantly learns from past orders, delays, and demand swings to choose better suppliers, order quantities, and delivery routes so materials arrive on time with less cost and waste.
Think of this as turning your marketing department into a super-targeted, always-on trading desk that continuously tests, learns, and optimizes where every dollar goes—using AI as the brain that watches all the data and adjusts in real time.
This is like giving your marketing team a very fast, very smart assistant that watches how customers behave across channels, figures out what works, and quietly adjusts your ads, emails, and targeting to get better results with the same budget.
It’s like an autopilot for your room rates: the system constantly watches demand, competitors, events, and booking patterns, then adjusts prices in real time to sell the right room to the right guest at the best possible price.
Imagine your sales team has a long line of people waiting outside the store, but only a few will actually buy. AI lead scoring is like a smart bouncer that looks at each person’s behavior and history, then quietly tells your reps, “Talk to these five first; they’re most likely to buy today.”
This is like giving your marketing team a crystal ball that looks at all your past customer and campaign data and says, “If you spend money here, with this message, to this audience, you’re most likely to get results.”
This is about using data to build a “crystal ball” for your marketing—software looks at past customer behavior and predicts who is likely to buy, churn, or respond to an offer so you can spend your budget where it’s most likely to work.
Imagine your whole supply chain—factories, warehouses, trucks, and suppliers—running like a smart GPS for your business. It constantly checks traffic (demand), fuel (inventory), and roadblocks (disruptions) and then suggests the best route and timing so you deliver on time with less waste and lower cost.
This is like having a super-smart media planner that reads every page, video, or app screen in real time and decides whether your ad should appear there based on how likely someone is to act (click, visit, buy) – all without using cookies or following people around the web.
Think of it as a super-smart calculator that constantly watches your competitors’ prices, your inventory, and shopper behavior, then suggests the best price for every product—while humans make the final strategic calls.
This is like a smart security system for banks that constantly watches transactions and customers to spot signs of money laundering or financial crime faster and more accurately than humans alone.
Imagine having a smart assistant that constantly watches how your people are doing, spots early warning signs that someone might quit, and suggests what you can do to keep them happy and engaged—before you lose them. That’s what AI for employee retention does.
Think of Pelico as an air-traffic control tower for a factory’s supply chain. It continuously watches orders, inventory, suppliers, and production, then tells planners and buyers where problems will appear and what to do about them before things go wrong.
Think of Apli as a smart hiring assistant that reads resumes, screens candidates, and moves them through the hiring funnel automatically so your recruiters only focus on the best-fit people.
This is like giving every sports fan a smart digital concierge that learns what they love—seats, merch, highlights, stats—and quietly adjusts the entire game-day and at-home experience around them.
Imagine your factory is a busy kitchen with many different dishes to cook. This system is like a super–smart head chef that constantly reorders which dishes to make first so the ovens are always full, the cooks never wait around, and customers still get their meals on time.
Like having a super-fast, tireless research nurse who can read thousands of charts in minutes and flag exactly which cancer patients qualify for which clinical trials.
Imagine your hiring team gets a smart co-pilot that reads every CV, compares it with the job needs, learns what ‘good hires’ looked like in the past, and then brings you a short, high-quality candidate list—while also warning you about possible bias and compliance issues.
This is like a smart assistant that reads a patient’s electronic medical record and quietly taps the doctor on the shoulder to say, “Based on all this history and lab data, this patient looks like they’re at high risk for X in the next few hours—here’s why and what to watch out for.”
Think of AI in clinical trials as a super‑organized project manager and data analyst that reads mountains of medical data, spots patterns faster than humans, and flags problems early so studies finish faster and safer.
Think of this as a smart co‑pilot for nurses: it watches patient data, compares it to what’s happened with thousands of similar patients before, and then suggests what to watch out for and what actions might be needed—while the nurse stays in full control.
Think of an AI ATS like a very fast, tireless recruiting assistant that reads every resume, ranks candidates, writes outreach messages, and keeps applicants moving through the hiring pipeline automatically, instead of recruiters doing it all by hand.
Like having a smart assistant that reads every clinical trial entry on ClinicalTrials.gov and turns the messy, technical listings into clean, searchable summaries and insights for sponsors and sites.
Think of AI recruitment as a super-fast digital hiring assistant that reads CVs, screens candidates, schedules interviews, and flags the best matches for a role – the way spam filters scan thousands of emails to find the ones you actually want.
Think of Findem as a supercharged hiring detective that scans millions of public signals about people and turns them into a short, qualified list of candidates who actually match what you need—skills, experience, and diversity goals—before your recruiters ever start manual sourcing.
This is like giving every salesperson a smart digital assistant that lives inside Microsoft Dynamics 365. It watches deals, emails, and tasks, then proactively suggests next steps, drafts outreach, and updates CRM records for them.
Think of this as putting a very smart assistant inside your CRM that watches all your customer interactions, predicts which deals are most likely to close, and nudges sales reps on what to do next and when.
This is about choosing a sales CRM that has a built‑in ‘smart assistant’—it watches all your customer interactions, predicts which deals to focus on, and automates follow‑ups so your reps sell instead of doing admin.
This is about turning your CRM (Microsoft Dynamics 365) into a smart sales assistant that watches all your customer data, predicts who to talk to next, and automates routine follow‑ups so your sales team can focus on closing deals instead of clicking buttons.
This is like giving your logistics and supply chain a smart autopilot: it constantly studies past deliveries, traffic, and orders to predict what will happen next and suggest the best routes, inventory levels, and staffing without humans having to crunch all the numbers.
Imagine your physical store behaving like your best online shop: it knows what customers like, keeps shelves stocked automatically, adjusts prices smartly, and helps staff answer any question – all using AI as an invisible assistant behind the scenes.
This is about using AI as an always‑on radar and autopilot for the supply chain: it constantly scans for risks (like delays, shortages, demand spikes), predicts problems before they hit, and suggests or triggers responses so the business can keep products flowing to customers.
This is like giving your factory a smart air-traffic controller that constantly looks at all your machines, workers, and orders, then automatically decides the best sequence of jobs so everything ships on time with minimal idle time and overtime.
This is like giving your supply chain a set of always‑on, ultra‑observant eyes and a smart brain that constantly checks what’s happening in stores and warehouses, predicts problems (like stockouts), and tells your teams exactly what to do to keep shelves full and inventory lean.
This is like giving your entire supply chain a smart control tower that can watch everything in real time, predict problems before they happen, and suggest the best next move across planning, sourcing, production, logistics, and inventory.
Like having a smart inspection manager that constantly reviews all trial data and documents, then tells your team where the real risks are so they inspect the right sites and patients first.
This is like giving your bank’s fraud and compliance team a super-smart assistant that reads every transaction in real time, remembers past patterns, and flags only the truly suspicious ones instead of overwhelming humans with noise.
Imagine watching all the money movements in a bank as if they were a big social network: people and companies are dots, and payments are lines between them. This system uses AI to spot unusual and suspicious patterns in that network—like circles of accounts passing money around in strange ways—so compliance teams can catch money laundering much faster and with fewer false alarms.
Think of this as a smart digital detective that constantly watches bank transactions and customer behavior, learning patterns of fraud and money laundering over time so it can flag suspicious activity far more accurately than rigid rule-based systems, while still staying within regulatory guardrails.
This is like a supercharged planning sandbox for delivery routes and vehicle schedules: you can try different ways of assigning trucks and drivers to trips on a computer, see how each plan performs, and then pick the best one before you spend real money on the road.
Think of this as a smart watchdog for banks: it constantly watches transactions and customer behavior, learns what “normal” looks like, and then flags suspicious activity that could be money laundering or fraud—much more accurately than old rules-based systems.
This is like having a super-calculator that helps design clinical trials which can change course mid-way—such as adjusting dosage or sample size—without breaking FDA rules or statistical rigor.
This is like an extremely fast, tireless credit analyst that looks at huge amounts of financial and behavioral data to predict how likely each customer is to pay late or default, so you can set smarter credit limits and terms automatically.
Like a smart dating app for clinical research, this AI reads people’s health records and trial requirements to quickly find the best matches between volunteers and studies.
Think of your supply chain planning as flying a modern plane: the AI is the autopilot doing millions of calculations per second, and your planners are the pilots deciding the destination, watching for storms, and overriding when needed. This setup makes planning faster, safer, and more precise than humans or software alone.
Kayros is like a super-smart air traffic controller for your factory. It constantly looks at all your machines, orders, and constraints, then automatically figures out the best possible production plan and schedule—and keeps adjusting it when things change.
This is like giving your warehouse a weather forecast for customer demand so it can stock the right products at the right time instead of guessing and getting caught in a storm of shortages or excess inventory.
Think of AI in clinical trials as an ultra-fast, tireless research assistant that helps pharma teams find the right patients, design better studies, monitor participants in real time, and clean up data much faster than humans alone—so new drugs get to patients sooner.
Imagine a very smart store manager who can see every product in every store and warehouse at once, predict where customers will actually buy it, and quietly shuffle inventory around before shelves go empty or stock piles up in the wrong place.
This is like giving drug development teams a super-smart assistant that can read piles of medical data, predict which patients and trial designs will work best, and continuously monitor results so trials finish faster and with fewer costly mistakes.
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 like giving your planning team a super-calculator that looks at years of sales, promotions, seasons, and external events to predict how much customers will buy next week, next month, and next season—far more accurately than traditional spreadsheets.
Think of this like a digital security team that never sleeps, watching every transaction in real time and using AI to spot subtle patterns that look like fraud or scams before humans would ever notice them.
This is like having a smart weather forecast, but for your store’s inventory. It looks at your past sales, seasons, promotions, and other patterns to predict how many units of each product you’ll need in the future so you don’t run out or overstock.
This is like giving every shopper their own digital sales associate who remembers what they like, what they looked at before, and what similar customers bought, then uses all that data to tailor offers, messages, and experiences in real time across stores, apps, and websites.