80 AI use cases • Executive briefs • Technical analysis
This is like upgrading your online store’s search bar so it understands shoppers the way a good salesperson does—by looking at both the words and the product pictures, not just matching text literally.
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 online store a smart digital stylist, photographer, and sales assistant that can instantly create product images, descriptions, and personalized messages for each shopper.
This is like giving your merchandising and planning team a super-smart assistant that constantly watches sales and stock levels across all channels, then tells you exactly what to move, discount, or reorder so you don’t run out of winners or get stuck with losers.
This is like giving your online store a smart digital marketer that automatically writes product descriptions, emails, and ads for you so you sell more without hiring a big marketing team.
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.
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 like a smart shop assistant for an online store that learns what each customer likes and then quietly rearranges the shelves for them—showing different products, bundles, and follow‑up suggestions before and after purchase, even around returns.
This is about giving every shopper their own ‘personal store window’ online. AI watches what each person browses, buys, clicks and ignores, then rearranges products, offers and content in real time so the site feels like it was built just for that one customer.
Think of it as a super-smart price tag system that constantly checks demand, competition, inventory, and customer behavior, then updates prices automatically to be as profitable and attractive as possible—like having your best pricing manager working 24/7 on every product.
Imagine every visitor walking into your online store and instantly seeing the products, offers, and content most relevant to them—like a smart shop assistant who remembers every past visit, what they liked, ignored, and bought, and rearranges the whole store in real time for that one person.
This is like putting thousands of tiny robot price managers on Amazon who constantly watch each other and change prices. The study analyzes how those robots behave in the real world and what that does to prices and competition.
This is like giving every seller on eBay a smart assistant that can (1) tell them what a fair price is for their item based on millions of similar listings, and (2) instantly show shoppers other items that are most similar to what they’re viewing or searching for.
Think of Lily AI as a smart retail stylist for your online store that understands products and shoppers the way a great in‑store associate does, then uses that understanding to improve search, recommendations, and product discovery.
Imagine a shopper can take a photo of a dress they see on the street, upload it to your online store, and instantly see similar dresses you sell—no need to guess keywords like “floral midi dress with puff sleeves.” That’s visual search for ecommerce.
This is Google adding an AI shopping helper that can guide customers from product discovery all the way through checkout, automatically filling in steps, suggesting options, and smoothing out the buying process inside Google’s shopping surfaces.
Imagine giving every part of your online store—merchandising, pricing, inventory, marketing—its own smart digital assistant that can watch what’s happening in real time and quietly fix or improve things without needing a person to click every button. That’s what agentic AI for ecommerce operations is about.
This is like giving your online store a smart brain that watches how every shopper browses and buys, then quietly adjusts prices, search results, and recommendations so each person sees what they’re most likely to want and buy.
Think of this as a digital marketing autopilot for online stores: it watches your ads, audiences, and creative 24/7, learns what works, then automatically shifts budget, tests new ideas, and reports results, so you sell more with less manual tweaking.
This is like hiring thousands of secret shoppers to check competitor prices every few minutes before and during Black Friday/Cyber Monday—then feeding that intel into a smart spreadsheet so you can automatically adjust your own prices to stay attractive and profitable.
This is about using AI to make online store products easier to find—both in Google and inside your own site—like having a smart store clerk who instantly knows what each shopper wants and rearranges the shelves in real time.
This is like a smart autopilot for your online store’s stock levels. It watches sales, seasonality, and trends, then tells you what to reorder, when, and how much, so you don’t run out or overstock.
This is like giving your inventory system (Zenventory) a smart assistant that can read all your product and operations data, spot patterns, and answer questions in plain English so teams can manage stock and orders faster and with fewer mistakes.
Think of this as a smart autopilot for your online product inventory. It watches your sales, predicts what will sell and when, and then tells you exactly how much stock you should have so you don’t run out or get stuck with excess inventory.
Imagine the checkout page of your online store acting like a smart salesperson who already knows what each shopper is likely to say “yes” to in the last 5 seconds before they pay. This system uses AI to decide, in real time, which offer, ad, or upsell to show on the checkout screen so it feels relevant—not spammy—and makes you more money from the same traffic.
This is about making every shopper’s online store experience feel like a helpful salesperson knows their tastes — showing the right products, offers, and content to each person instead of the same generic website for everyone.
Imagine every shopper in your online store having a smart salesperson who remembers their tastes, budget, and goals, and quietly reorders the search results and product suggestions just for them every time they type in the same vague query like “running shoes.”
This is like having a smart digital sales associate that quietly watches how people browse, search, and compare products across apps and websites, then helps brands put the right message or product in front of the right shopper at the right time as they move from “just looking” to “I’m ready to buy.”
Think of this as an autopilot for your online store’s prices: it watches demand, competitors, and costs in real time, then suggests or applies the ‘right’ price for each product to maximize profit without scaring away customers.
This is like having a tireless digital scout that constantly checks competitors’ prices across the internet, compares them to yours, and suggests how you should price your products to stay competitive and profitable.
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 Alibaba.com getting a super-smart digital buying assistant that doesn’t just answer questions, but can actually help run parts of the buying and selling process for you — from finding the right suppliers to lining up orders and follow‑ups, almost like giving every buyer and seller a junior operations team inside the platform.
Think of this as a smart, always‑on stockroom manager that watches sales, predicts what will sell next, and automatically reorders the right products so you don’t run out or overstock.
This is like an always‑on smart salesperson that constantly watches demand, competitors, and stock levels, then automatically adjusts your product prices to hit your goals (more profit, more volume, or both) without a human changing prices all day.
This is like giving your online store a smarter salesperson who understands spoken questions (voice search) and photos (visual search), then guides shoppers to exactly what they want so they’re more likely to buy.
Think of this as a super-smart price-watching assistant that constantly scans your competitors’ online prices and product assortments, then tells you how to adjust your own prices to stay competitive and profitable—without a human staring at spreadsheets all day.
Think of an AI shopping assistant as a smart, always-on store associate that lives inside your website or app. It chats with customers, understands what they want (even if they’re vague), recommends the right products, and can walk them all the way through to checkout.
Think of MOON Embedding as a smarter matchmaking system between what shoppers type (and see) and the ads you show them. Instead of just using keywords, it learns a shared ‘language’ across text, images, and other signals so the ad engine can understand what a shopper really wants and pick the most relevant product ad in real time.
This is like an online shop or airline that quietly adjusts prices for each customer the way a skilled market trader does—watching how you browse, what you’ve bought before, and how urgent you seem—then offering a price it thinks you’ll accept right now.
This is like giving your Shopify development team a smart co‑pilot that helps design the store, write product copy, generate images, and optimize performance so new features launch faster and sell better.
Think of this as a smart autopilot for your store’s stock: it constantly learns what sells where and when, then quietly adjusts what you buy, how much you hold, and where you place it so you’re rarely out of stock and rarely stuck with leftovers.
This is like an automatic price manager for an online store that constantly watches demand, competition, and inventory, then adjusts prices up or down to maximize profit and sales—similar to how airline ticket prices change all the time.
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.
Think of COSMO as Amazon’s ‘common sense brain’ for shopping: it teaches computers the everyday knowledge humans use when browsing products (like knowing that hiking boots go with rainy weather, or that a phone case should fit a specific phone model) and then uses that knowledge to make search, recommendations, and product understanding much smarter.
This is like letting shoppers show your store a picture of what they want instead of typing words. The AI then finds the closest matching products across your catalog in seconds.
Think of this as a map of all the ways online stores are using AI today—like a guidebook that explains how Amazon‑style recommendations, smart pricing, chatbots, and fraud checks actually work and where they’re going next.
Prediko is like a smart autopilot for your Shopify store’s stock. It looks at your sales, seasonality, and upcoming campaigns, then tells you what to buy, when to buy it, and how much, so you don’t run out of best-sellers or overstock slow movers.
This is like letting shoppers use pictures instead of words to find products online. A customer snaps or uploads a photo of shoes they like, and the store instantly shows the closest matches you sell.
Think of your online store or booking site as a hotel front desk clerk who sees all reservations coming in. This “clerk” watches how early people book, what they add to their cart, and how full the inventory is getting, then decides in real time which extras (upsells) to offer and at what price to maximize total revenue without scaring customers away.
This is like giving your warehouse a smart assistant that constantly checks what is selling fast or slow and then tells you exactly how much of each product to keep, so you don’t run out and you don’t end up with piles of unsold stock.
Think of MOON2.0 as a very smart “product librarian” for an online store that learns from both pictures and text (titles, descriptions, attributes) at the same time. Instead of favoring just images or just text, it dynamically balances both so it can better understand what each product really is, how it should be grouped, and when two listings are actually the same thing.
This is like giving your warehouse and supply chain a crystal ball that predicts what customers will buy and when, then automatically adjusts stock levels so you don’t run out or overstock.
Think of this as a smart control tower for your ecommerce warehouse: it connects all your data (orders, inventory, shipping, labor), continuously analyzes it, and tells you how to store products, pick orders, and schedule staff so everything moves faster and cheaper.
This is like giving your warehouse and supply chain a smart autopilot that constantly predicts what stock you’ll need, where, and when—so shelves are rarely empty, and you’re not overstuffed with products that don’t sell.
This is like giving your online store a smart shop assistant who instantly understands what customers are looking for—even if they type vague, messy, or unconventional search terms—and then shows the most relevant products first.
This is like giving your eCommerce analytics team a smart assistant that you can ask plain‑English questions such as “Why are conversions down this week?” or “Which campaigns are driving the highest LTV customers?” and it instantly pulls the right data, runs the analysis, and explains the answers back to you.
This is about using AI as a smart digital staff for an online store – it helps with the boring back‑office work like bookkeeping and inventory, and also helps write product descriptions, emails, and ads in your brand’s voice so humans can focus on higher‑value work.
Imagine a smart store manager who constantly watches what customers are buying, what competitors are charging, and how much stock you have left—and then adjusts your prices and reorders inventory automatically every hour to maximize profit while avoiding stockouts and dead stock.
This is like giving every online shopper a smart personal sales assistant that quietly watches what they look at and buy, then suggests the right products at the right time to increase what ends up in the cart.
This is like an online store’s version of airline ticket pricing: the price of a product can automatically go up or down during the day based on demand, competition, and stock levels instead of staying fixed.
Imagine every shopper who visits your online store getting their own smart salesperson who already knows their tastes, budget, and past behavior, and quietly rearranges the entire store so their favorite items show up first—on the homepage, in search results, and in emails.
This is like giving every product image in your online store a super-smart labeler and matchmaker. Instead of just relying on text keywords, AI looks at the actual picture (colors, style, shape, context) so customers can find the right products even if they search with vague terms or by uploading similar photos.
This is like using Shazam but for shopping: you snap or upload a photo of an item you like, and the app finds similar listings for sale on Mercari.
This is like giving your warehouse and purchasing team a smart autopilot. It watches sales, stock levels, and supply patterns over time, then recommends (or automatically decides) how much of each product to order and when, so you don’t run out or overstock.
This is about teaching an online store to change its prices the way airlines change ticket prices—automatically adjusting based on demand, competition, and shipping/logistics costs so you don’t leave money on the table or scare customers away.
This is about search moving from “blue links on Google” to AI helpers that immediately show the right product, store, or app—no scrolling, no guessing. Think of it as your own smart shopper that understands what you want, where you are, and what device you’re on, then jumps straight to the best answer or product.
This is like an always-on smart price tag system for online stores. It watches demand, competitor prices, seasonality, and inventory, then automatically nudges prices up or down to hit revenue or margin goals—similar to how airline or ride‑sharing prices change in real time.
Imagine you run an online marketplace of AI chatbots (LLMs) and customers can choose between several providers based on price and quality. This research treats that situation like a strategic game: providers set prices first, customers react by routing their traffic to the best-value options, and the model finds the right pricing strategy that maximizes revenue while keeping demand flowing efficiently across providers.
Imagine a smart camera system in your stores that continuously counts what’s on shelves and back rooms, spots when items are running low or misplaced, and feeds that information into your inventory systems so you always know what you really have — without employees walking around with clipboards or scanners.
Think of InveTrack as a smart stockroom assistant for online sellers: it watches what’s coming in and going out, predicts when you’ll run low, and helps you reorder the right products at the right time so you don’t run out or overstock.
This is about using AI as a fast, smart photo studio for online stores—so marketers can clean up, resize, and restyle product photos at scale instead of doing it one by one in Photoshop.
Think of it as a smart assistant that watches your sales and stock levels, then tells you how much to order and when so you don’t run out or overstock—like a weather forecast, but for your inventory.
Think of AI in ecommerce as a smart digital salesperson, merchandiser, and operations manager that watches what every shopper does and then automatically adjusts product suggestions, prices, ads, and support for each person in real time.
This is a guide that shows online stores how to let ‘smart robots’ handle repetitive ecommerce work — from answering common customer questions to recommending products and updating inventory — so humans can focus on strategy and creativity.
Think of this as a toolbox of AI ‘assistants’ for an online store: one helps shoppers find the right products, one writes better descriptions and emails, and another watches for fraud or churn risk in the background.
This is a strategy-style overview describing how a luxury brand like Burberry can use AI across its online store – for example, to recommend products, personalize the website, and improve customer service – rather than a single, concrete software product.
This is a buyer’s guide that lists and explains different AI tools online retailers can plug into their stores to automate things like product descriptions, customer support, pricing, and marketing—like hiring 25 specialized digital assistants for different parts of your eCommerce operation.
This is about using AI as a smart digital salesperson and operations manager for an online store. It learns from customer behavior and product data to show the right products, answer questions, set better prices, and automate routine work.
Think of this as turning an online store into a ‘self‑driving’ business: AI quietly watches what customers do, predicts what they’ll want, adjusts prices and content in real time, and automates support and operations so people only handle the tricky edge cases.
This article is like a buyer’s guide that walks an online store owner through the main types of AI helpers they can plug into their shop—one to talk to customers, one to suggest products, one to write marketing copy, one to manage pricing, etc.—so the store can sell more with fewer people doing manual work.