As artificial intelligence becomes more and more mainstream, companies are aggressively using AI for retail operations. From the stockroom to the storefront, AI for retail is no longer a futuristic buzzword but a foundational technology that enables businesses to operate with unprecedented efficiency, personalization, and customer insight. By leveraging machine learning algorithms, computer vision, and natural language processing, retailers can now predict trends, automate complex processes, and create hyper-personalized shopping experiences that were once the stuff of science fiction.
How AI For Retail Is Being Used
AI for retail is being deployed across multiple facets of the industry:
- Personalized Shopping: AI analyzes customer behavior to offer tailored product recommendations.
- Inventory Management: Predictive analytics help retailers optimize stock levels and reduce waste.
- Customer Service: Chatbots and virtual assistants handle inquiries 24/7.
- Visual Search: Shoppers can upload images to find similar products instantly.
- Fraud Detection: AI detects suspicious transactions in real time.
- Checkout-Free Stores: Cashier-less technology speeds up the shopping process.
AI For Retail: 18 Most Prominent Tools
1. Salesforce Einstein
Salesforce Einstein is not a standalone product but an integrated layer of AI technology built into the core of the Salesforce platform. It leverages all the customer data within a retailer’s CRM—from purchase history to service interactions—to deliver predictive insights and automate tasks. This powerful application of AI for retail helps businesses understand customer behavior, predict future sales, and personalize marketing campaigns at scale. By embedding intelligence directly into business workflows, it empowers employees to make smarter, data-driven decisions.
- Prominent Clients: Adidas, L’Oréal, Godiva.
- Real-World Example: A sporting goods retailer uses Salesforce Einstein to power its email marketing. The AI analyzes a customer’s Browse history (e.g., looking at running shoes) and recent purchases. Einstein then automatically sends a personalized email featuring new arrivals in running shoes and complementary products like performance socks, significantly increasing the likelihood of a conversion. This is a prime example of leveraging AI for retail to enhance marketing ROI.
2. Dynamic Yield
Dynamic Yield, a Mastercard company, is a specialized platform focused on creating individualized digital customer experiences. It uses AI to personalize every customer interaction across web, mobile apps, and email. The platform’s algorithms analyze user data in real-time to deliver custom product recommendations, tailored promotional banners, and dynamically tested site layouts. For businesses looking to optimize conversions, Dynamic Yield represents a critical tool in the AI for retail toolkit.
- Prominent Clients: Under Armour, Sephora, Urban Outfitters.
- Real-World Example: An online fashion retailer uses Dynamic Yield to personalize its homepage. A visitor from a cold climate like Stockholm might see a banner promoting winter coats, while a visitor from sunny Jaipur sees ads for sunglasses and t-shirts. This real-time adaptation, powered by AI for retail, ensures content is always relevant and engaging.
3. Blue Yonder
Blue Yonder is a titan in the world of supply chain management, using AI and machine learning (ML) to help retailers forecast demand, manage inventory, and optimize logistics. Its Luminate Platform analyzes thousands of variables, including weather patterns, social media trends, and local events, to create incredibly accurate demand forecasts. This advanced forecasting is a game-changer for AI for retail, helping to prevent both stockouts and costly overstock situations.
- Prominent Clients: Walmart, Marks & Spencer, Coca-Cola.
- Real-World Example: A major grocery chain uses Blue Yonder to prepare for a regional festival. The AI predicts a surge in demand for specific items like sweets and beverages by analyzing historical sales data, local event calendars, and even social media chatter. The system then automatically recommends increasing inventory levels for those items in specific stores, ensuring they can meet customer demand. This showcases the predictive power of AI for retail in supply chain operations.
4. Ada
Ada is an AI-powered customer service automation platform designed to handle a high volume of customer inquiries without human intervention. It uses Natural Language Processing (NLP) to understand customer intent and provide instant, accurate answers to common questions about order status, return policies, and product details. By automating these routine interactions, Ada frees up human agents to handle more complex issues, making it a vital efficiency tool for AI for retail.
- Prominent Clients: Zoom, Shopify, AirAsia.
- Real-World Example: A large electronics retailer integrates Ada’s chatbot into its website. During a major product launch, thousands of customers simultaneously ask, “When will my new phone ship?” Instead of overwhelming the support team, the Ada-powered bot instantly provides the correct shipping timeline to each customer, maintaining a positive customer experience during a high-traffic period. This automated support system is a practical application of AI for retail.
5. Syte
Syte specializes in visual AI technology, transforming the way customers search for and discover products. Users can take a photo of an item they see in the real world, and Syte’s visual search engine will find the exact or similar items within a retailer’s inventory. This technology bridges the gap between online and offline inspiration, making the entire world a shoppable experience. This approach to product discovery is a visually intuitive form of AI for retail.
- Prominent Clients: Prada, Farfetch, Castorama.
- Real-World Example: A shopper sees someone wearing a pair of boots they love. They discreetly take a picture and upload it to a fashion retailer’s app that uses Syte. The app instantly displays the exact pair of boots for sale, along with visually similar alternatives at different price points. This “snap-to-shop” capability is a powerful use of AI for retail that drives impulse purchases.
6. Trigo
Trigo is at the forefront of bringing autonomous checkout technology to brick-and-mortar stores. Using a network of overhead cameras and sophisticated computer vision algorithms, Trigo’s system allows shoppers to simply walk into a store, pick up the items they want, and walk out without ever visiting a checkout counter. The AI automatically identifies the products taken and charges the customer’s account. This frictionless experience is a revolutionary implementation of AI for retail.
- Prominent Clients: Tesco, REWE, Aldi Nord.
- Real-World Example: A Tesco grocery store in London is equipped with Trigo’s technology. A customer scans a QR code on their app to enter. As they place items like milk, bread, and apples into their bag, ceiling-mounted cameras track the selections. When they leave, their app is automatically charged for the correct items, completely eliminating checkout lines. This is how AI for retail is reshaping the physical store experience.
7. Riskified
Riskified is an e-commerce fraud prevention platform that uses AI to distinguish legitimate customers from fraudsters. Every online order is analyzed in real-time, with the AI making an instant “approve” or “decline” decision. This helps retailers maximize revenue by safely approving more orders while protecting themselves from chargebacks and other forms of fraud. In the high-stakes world of online payments, Riskified is an essential security layer of AI for retail.
- Prominent Clients: Macy’s, Wish, Gymshark.
- Real-World Example: During a Black Friday sale, an online retailer is flooded with orders. A fraudster attempts to use stolen credit card information to make multiple high-value purchases. Riskified’s AI instantly identifies the anomalous behavior—such as an unusual shipping address and rapid-fire purchase attempts—and declines the transactions, while simultaneously approving thousands of legitimate orders. This precision demonstrates the value of AI for retail in securing revenue.
8. Wiser Solutions
Wiser provides retailers with actionable data for pricing, promotion, and marketing decisions. Its AI platform scrapes and analyzes competitor pricing data from across the web, allowing retailers to implement dynamic pricing strategies. The tool can automatically adjust a product’s price based on competitor prices, inventory levels, and demand to maximize profit margins. Competitive intelligence is a key area where AI for retail provides a significant advantage.
- Prominent Clients: Castrol, Kellanova (formerly Kellogg’s), Energizer.
- Real-World Example: An online seller of consumer electronics uses Wiser to monitor the prices of a popular headphone model on Amazon and other major retail sites. Wiser’s AI automatically adjusts the seller’s price to remain competitive—lowering it slightly to win the sale or raising it when competitors run out of stock. This automated, market-aware pricing strategy, enabled by AI for retail, ensures optimal profitability.
9. Algolia
Algolia is an AI-powered search and discovery platform that delivers incredibly fast and relevant search results on a retailer’s website or app. Unlike traditional keyword-based search, Algolia’s AI understands user intent, handles typos, and provides smart filtering and ranking to help customers find what they’re looking for instantly. A seamless search experience is fundamental to e-commerce success, making this a crucial application of AI for retail.
- Prominent Clients: LVMH, Decathlon, Lacoste.
- Real-World Example: A customer on a large home improvement store’s website types “rwod scrws” instead of “wood screws.” A basic search engine might return no results. Algolia’s AI-powered search instantly corrects the typo, understands the user is likely looking for screws meant for wood, and displays the most relevant products first. This forgiving and intelligent search function, driven by AI for retail, prevents customer frustration and reduces site abandonment.
10. Zebra Technologies
Zebra Technologies provides a wide range of solutions for the retail floor, including AI-powered robotics and data capture tools. Their “SmartSight” intelligent automation system, for example, is a robot that autonomously navigates store aisles to identify out-of-stock items, pricing errors, and misplaced products. This automates a tedious manual task, ensuring shelf integrity and freeing up employees for customer-facing roles. This is a perfect example of how AI for retail can optimize physical store operations.
- Prominent Clients: Many of the world’s largest retailers rely on Zebra’s hardware and software, often integrated into their own systems.
- Real-World Example: A large supermarket deploys a Zebra robot overnight. The robot patrols every aisle, scanning shelves. Its AI identifies that a popular cereal brand is out of stock on the shelf but available in the stockroom and notes a misplaced item in the dairy aisle. This data is sent to employees’ handheld devices, allowing them to restock and correct errors before the store opens, ensuring a better shopping experience through the use of AI for retail.
11. IBM Watson Commerce (now HCL Commerce)
HCL Commerce, which incorporates the powerful AI capabilities of IBM Watson, is an enterprise-grade e-commerce platform designed to create intelligent, personalized customer journeys. It leverages AI to analyze customer behavior, personalize product recommendations in real-time, and optimize merchandising strategies. The platform’s strength lies in its ability to manage complex B2B and B2C environments, using AI to tailor everything from catalogs and pricing to targeted promotions for different user segments. This robust platform is a comprehensive solution for businesses looking to deploy AI for retail.
- Prominent Clients: (Historically) The Home Depot, Carhartt, Brooks Brothers.
- Real-World Example: A B2B supplier of office equipment uses the platform’s AI to provide a unique experience for each corporate client. When an employee from a large tech firm logs in, they see a custom catalog with pre-negotiated pricing. The AI also analyzes the firm’s past orders and recommends replenishing ink cartridges and paper, streamlining their procurement process. This is a sophisticated application of AI for retail in a B2B context.
12. Amazon Rekognition
Amazon Rekognition is a powerful and versatile computer vision service from Amazon Web Services (AWS) that makes it easy to add image and video analysis to applications. While not exclusively a retail tool, it serves as a foundational technology for countless retail solutions. It can identify objects, people, text, scenes, and activities in images and videos. Retailers use it for everything from content moderation of user reviews to in-store analytics and powering visual search. For developers building the next generation of shopping experiences, Rekognition is a key building block for AI for retail.
- Prominent Clients: Pinterest, Zillow, and it powers parts of Amazon’s own retail operations.
- Real-World Example: A fashion marketplace allows users to upload photos of their outfits. They use Amazon Rekognition to automatically scan these images to detect and flag inappropriate content. The AI also identifies key attributes like “red dress,” “handbag,” and “sneakers,” automatically tagging the content to make it more discoverable for other users, showcasing a practical safety and operational use of AI for retail.
13. ViSenze
ViSenze is another leading AI company specializing in visual search and discovery for the retail industry. Its platform empowers retailers to make their visual content shoppable, whether it’s on their own website, in social media feeds, or within digital publications. Beyond simple image matching, ViSenze’s AI can recognize multiple items within a single image and provide personalized recommendations based on a user’s visual style. This technology transforms passive content consumption into an active shopping opportunity, representing a major advancement for AI for retail.
- Prominent Clients: H&M, Zalora, Rakuten.
- Real-World Example: A major online furniture retailer partners with an influential home decor blog. Using ViSenze, every image on the blog becomes interactive. A reader can hover over a lamp in a photo of a living room, and a pop-up appears with a direct link to purchase that exact lamp from the retailer’s site. This seamless integration of content and commerce is a highly effective strategy for AI for retail.
14. Dynamic Yield (by McDonald’s)
Dynamic Yield, a Mastercard company and formerly owned by McDonald’s, remains a premier AI-powered personalization platform. Its acquisition by McDonald’s famously brought AI-driven menu recommendations to the drive-thru, showcasing its power in physical retail. The platform excels at omnichannel personalization, creating a consistent and tailored experience for customers whether they are on a website, using a mobile app, or interacting with an in-store kiosk. This ability to unify the customer journey is what makes it such a potent tool for AI for retail.
- Prominent Clients: McDonald’s, IKEA, Office Depot.
- Real-World Example: A customer browses for a specific bookshelf on a home goods retailer’s website but doesn’t buy it. Later that week, they visit a physical store. When they log into an in-store kiosk to check for stock, Dynamic Yield’s AI recognizes them and displays a personalized message on screen: “Still thinking about the Billy Bookcase? It’s in stock in Aisle 7.” This is a fantastic example of using AI for retail to bridge the online-offline gap.
15. Zebra Technologies’ AI Solutions
Beyond their shelf-scanning robots, Zebra Technologies offers a suite of AI solutions focused on optimizing store operations and empowering the workforce. Their prescriptive analytics tools, for example, don’t just report what happened—they recommend specific actions to improve outcomes. The AI analyzes data from inventory systems, staff schedules, and real-time store sensors to predict operational bottlenecks and guide managers on the best course of action. This directive intelligence is a highly practical form of AI for retail.
- Prominent Clients: Used widely across the retail and logistics sectors, including by major players like Walgreens and Kroger.
- Real-World Example: A manager at a large retail distribution center receives an alert from Zebra’s prescriptive analytics software. The AI has analyzed incoming truck schedules and current order-picking speeds and predicts a major bottleneck in the shipping bay in three hours. The system recommends reassigning two specific workers from the receiving dock to the shipping area for the next two hours to prevent the delay. This proactive guidance is a powerful use of AI for retail to enhance efficiency.
16. Coveo
Coveo is an AI-powered relevance platform that goes beyond search to personalize the entire digital experience. It unifies content and data from various sources (product catalogs, help articles, user reviews) to understand user intent and deliver the most relevant information at every touchpoint. For retailers, this means not only better product search results but also proactive recommendations, personalized content, and more effective self-service options for customers. Coveo’s holistic approach to relevance makes it a transformative AI for retail platform.
- Prominent Clients: MAC Cosmetics, Xero, Paul Smith.
- Real-World Example: A customer searches for “4K TV” on an electronics retailer’s website. The Coveo-powered platform returns relevant TV models, but it also proactively displays a “Buying Guide for 4K TVs,” positive customer reviews for the top-rated models, and recommends a compatible soundbar—all on the same results page. This comprehensive response, powered by AI for retail, helps the customer make a confident purchase decision.
17. NVIDIA Metropolis
NVIDIA Metropolis is not a single product but an application framework and partner ecosystem that allows businesses to build and deploy advanced AI and computer vision applications. It provides the building blocks—including pre-trained models and software development kits—for creating solutions for intelligent video analytics. In retail, this enables everything from advanced loss prevention and queue management to tracking real-time shopper behavior for layout optimization. Metropolis is the engine that powers many custom, high-performance AI for retail solutions.
- Prominent Clients: As a framework, it’s used by solution developers and major retailers like Walmart to build their own custom AI applications.
- Real-World Example: A large shopping mall operator uses a custom solution built on NVIDIA Metropolis to analyze video feeds from cameras across the property. The AI identifies real-time foot traffic patterns, measures queue lengths at the food court, and detects crowd density. This data provides insights to mall management, helping them adjust staffing for cleaning crews and security, and providing valuable analytics to their retail tenants. This large-scale analysis is a key benefit of AI for retail.
18. Standard AI (formerly Standard Cognition)
Standard AI is a leading provider of autonomous checkout technology, enabling a “grab and go” shopping experience. What distinguishes Standard AI is its AI-only, camera-first approach, which does not require any shelf sensors, making it easier and more cost-effective to retrofit existing stores. The system uses advanced computer vision powered by ceiling-mounted cameras to accurately track shoppers and the products they select. This focus on retrofitting makes frictionless shopping accessible to a wider range of retailers and is a crucial innovation in AI for retail.
- Prominent Clients: Circle K, Compass Group.
- Real-World Example: A Circle K convenience store in an airport terminal is outfitted with Standard AI. A time-crunched traveler enters the store, picks up a bottle of water, a snack, and a magazine, and simply walks out. The camera-based system correctly identifies all the items and automatically bills their credit card on file via the store’s app, allowing them to get to their gate without waiting in a line. This is the future of convenience, made possible by AI for retail.