Mentioned in 61 AI use cases across 15 industries
Think of your online store as a smart salesperson who knows every customer’s tastes, can instantly tidy and rewrite your product catalog, and can answer questions 24/7 in natural language. This article describes how to bolt that salesperson’s “AI brain” onto a typical ecommerce site using search, recommendations, and automation.
Think of this as a smart control tower for mining and other heavy industries that watches your environmental, social, and operational data in one place and uses AI to flag risks and opportunities before they impact production or reputation.
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.
Think of this as a super-smart test analyst that reads your SAP setup, business processes, and change logs and then writes, updates, and runs SAP test cases for you—so your team mainly reviews and approves instead of building everything by hand.
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.
Think of this as a playbook for how wholesalers and B2B sellers can use ‘smart helpers’ across their online shop – from suggesting the right products to automating pricing and support – so the digital channel behaves more like a top human salesperson who never sleeps.
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 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 like having a super-accurate weather forecast, but for customer demand and store inventory: it predicts what products you’ll sell and tells you how much to stock and where, so shelves are full when customers arrive without overfilling the warehouse.
This is like giving every retail store manager a super‑smart digital co‑pilot that constantly walks the aisles in software: it spots what’s wrong with shelves, pricing, and promotions, then automatically kicks off the work in your business systems to fix it.
This is like having a super-smart store manager who can look at all your sales, seasons, and trends at once and then tell you exactly how much of each product to order, where to put it, and when to move it, so you never run out or overstock.
This is like an early‑warning system for phone and internet providers: it studies past customers who left and learns patterns so it can flag which current customers are most likely to cancel soon, giving the company time to intervene with offers or service improvements.
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 a smart early‑warning system for telecom companies that watches customer behavior and complaints, predicts who is likely to cancel soon, and tells your team exactly which customers to contact and what offers or actions will keep them from leaving.
Think of it as a super-fast digital recruiter that scans huge piles of resumes and job descriptions in seconds, shortlists the best matches, and keeps candidates moving quickly through the hiring process instead of getting stuck in inboxes and spreadsheets.
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 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 your HR system a smart assistant that can scan resumes, predict staffing needs, flag potential retention risks, and recommend the right people for the right roles, instead of HR teams doing all of that manually in spreadsheets and emails.
Think of this as turning your company’s HR data into a ‘smart advisor’ that spots patterns in hiring, performance, and turnover so leaders can make better people decisions instead of guessing from spreadsheets.
This is like giving your supply chain a smart GPS and weather system that constantly looks ahead, finds the fastest and safest routes for parts and materials, and automatically reroutes when there’s a disruption (factory shutdown, port delay, raw‑material shortage).
This is describing a ‘smart HR department in a box’ that uses AI and data analytics to sift CVs, predict employee issues, and automate routine HR work so people leaders can focus on people instead of paperwork.
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 store a very smart assistant that looks at past sales, seasons, and trends to guess how much of each product you’ll need—and then keeps adjusting that guess every day so you don’t run out or overstock.
This is like a weather forecast, but for store sales: it uses past sales data and patterns (seasonality, holidays, promotions) to predict how much you’ll sell in the future at each store or channel.
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.
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.
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 this as turning a manual, paper-heavy hiring process into a smart filter and assistant that helps recruiters scan resumes, rank candidates, and communicate faster, while also flagging potential bias or legal issues.
Think of this as a smart coach for your field salesforce that watches everyone’s activity and results, then quietly tells each rep: “Do this next, in this territory, with this product, because it’s most likely to hit your quota.”
This is like a smart crystal ball for retailers: it looks at your past sales, promotions, seasons, and external factors, then predicts how much of each product you’ll need in the future so you don’t run out or overstock.
This is like giving a store a crystal ball that uses past sales and promotions to guess how many items customers will buy in the future, so they stock just the right amount.
This is like an early-warning radar for employee resignations. It looks at patterns in engagement, feedback, and HR data to flag people or teams that are likely to quit soon so you can intervene before you lose them.
Think of this as teaching retail systems to ‘learn’ from sales, customer, and inventory data the way a great store manager does—spotting patterns in what people buy, when they buy, and what makes them come back, then using that to decide prices, promotions, and stock levels automatically.
This is like giving your power plant or energy equipment a “check engine” light that warns you days or weeks before something breaks, instead of after it fails. Sensors continually watch vibration, temperature, pressure, etc., and machine‑learning models learn the normal patterns so they can flag early signs of trouble.
Think of it as a smart thermometer for your remote workforce’s mood and engagement. It quietly reads signals from surveys, chats, check-ins, and activity data to tell managers who’s thriving, who’s checked out, and where to intervene before problems blow up.
Think of Orbitae AI as a smart control tower for an automotive company’s data. It connects to all your scattered data sources (production, sales, after‑sales, supply chain), lets managers ask questions in natural language, and then turns complex analytics into simple dashboards, forecasts, and recommendations to run the business better and faster.
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.
This is like giving European police a supercharged search and pattern-spotting engine that can sift through huge piles of digital information—messages, photos, travel records, financial data—to flag suspicious links between people, places, and events that humans would struggle to see in time.
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.
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.
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 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.
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.
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.
Think of this as turning your marketing from guessing to GPS navigation. Instead of marketers guessing what customers might want, AI and predictive analytics study past behavior (clicks, purchases, time on site) to forecast what each person is likely to want next and automatically adjust campaigns, channels, and offers in real time.
This is like giving every salesperson a smart, trustworthy assistant that lives inside their CRM. It listens to all the data in your sales boards, summarizes what’s important, predicts which deals need attention, and drafts the next emails or follow‑ups for you, while keeping managers in control of what AI can and can’t do.
This tool is like an automated marketing analyst that studies all your customer data and groups people into smart, predictive segments so you can send the right message to the right audience at the right time.
This is like a smart shopkeeper who remembers each regular customer and quietly adjusts offers and prices based on their habits, loyalty, and sensitivity to price—so they buy more and stay longer, while the shopkeeper still protects their overall profit across the whole supply chain.
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.
This is like hiring a smart mechanic that constantly listens to all your vehicles and equipment, predicts what’s about to break, and schedules repairs before anything actually fails or delays service.
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 learner having a personal tutor who watches how they learn, what they get right or wrong, how fast they move, and then quietly rearranges the course so they only see what they need next. That’s adaptive learning inside an LMS: the course reshapes itself in real time for each person.
Think of this as a smart shop assistant built into your online store that quietly watches what each shopper does and then rearranges the shelves, product lists, and offers in real time so each person sees the items they’re most likely to buy.
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.
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.
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.
This is like giving your global supply chain a smart GPS and co‑pilot: it constantly looks at all the data (demand, inventory, shipping, risks), simulates options, and recommends the best decisions instead of people doing it all in spreadsheets and emails.
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.
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 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.
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.