Artificial Intelligence in Retail

AI in the retail industry means better experiences, accurate forecasting, and automated inventory management.

An Overview of AI in Retail:

  • AI is enabling retail systems to work together to optimize customer experiences, forecasting, inventory management, and more.

  • AI technologies like computer vision bring near-real-time intelligence to brick-and-mortar stores. That same data, when analyzed in the cloud, can provide additional business insights.

  • Intel® technologies enable a wide range of AI capabilities, including intelligent display ads, smart shelves, endless aisle kiosks, enhanced inventory control, and smart self-checkout.


Artificial intelligence (AI) is reinventing the retail landscape. From using computer vision to customize promotions in real time to applying machine learning for inventory management, retailers can harness AI to connect with their customers and operate more efficiently. Intel® technologies power AI in retail at every step of the way, from the brick-and-mortar edge to the cloud.

To compete today, retailers must respond to their customers like never before, all while eliminating waste and inefficiencies from their operations. Data can you get there, but making sense of the sheer volume of it takes serious intelligence.

Digital transformation in retail is about more than connecting things. It’s about converting data into insights, which inform actions that drive better business outcomes. AI in retail—including machine learning and deep learning—are key to generating these insights. For retailers, that leads to incredible customer experiences, opportunities to grow revenue, fast innovation, and smart operations—all of which help differentiate you from your competitors.

Plenty of retailers are already using AI in some part of their operations. You might use AI in CRM software to automate marketing activities, or predictive analytics to identify which customers are likely to buy certain products. The cloud enables AI workloads that require volumes of data from many different sources to be stored and processed. Some examples of cloud retail workloads are demand forecasting machine learning and online product recommendations.

But running AI in the store itself offers advantages. Edge computing in retail acts as a catalyst of insight, aggregating and transforming massive volumes of raw data into valuable, actionable intelligence. Imagine inventory robots that automatically restock shelves; digital signage that adapts to the audience; and sensors that track customer traffic patterns to inform cross-selling and upselling opportunities.

A special type of AI deep learning in retail known as computer vision is gaining traction at brick and mortar. Computer vision “sees” and interprets visual data, giving you eyes where you need them. And it’s opening the door for new retail use cases across customer experience, demand forecasting, inventory management, and more.

Customer Experiences that Are Convenient and Personal

Whether it’s a small boutique or a multinational superstore, retailers work hard to create shopping experiences that are convenient, personalized, and enjoyable. Customers should be able to quickly find what they’re looking for, get help when they need it, and check out fast. AI streamlines these activities to help create more satisfying customer experiences.

For example, shoppers may be concerned about picking up germs from point of sale (POS) systems. But what if they could check out without touching anything? Computer vision makes it possible to accurately “see” items in a customer’s cart.

Digital signage embedded with computer vision can also measure customer engagement and serve up real-time advertising that speaks to the audience.

From the retail edge to the cloud, AI means more opportunities to personalize experiences. A POS system captures data about what was purchased that is used to generate new product recommendations for a given customer. Digital signage collects data about which types of customers are shopping and when, so that merchandising can make better decisions about product promotions. All this leads to more accurate segmentation and experiences that are tailored to a customer’s patterns and preferences.

Demand Forecasting and Merchandising

The more you understand customer behaviors and trends, the better you can meet demand and present the best possible products. AI helps retailers improve demand forecasting, make pricing decisions, and optimize product placement. As a result, customers connect with the right products, in the right place, at the right time. Predictive analytics can help you order the right amount of stock so that stores won’t end up with too much or too little. AI can also track data from online channels, informing better e-commerce strategies.

New types of AI at the retail edge help you recognize customer intent and optimize the shopper’s journey accordingly. One example is heat mapping in the store. The combination of cameras and computer vision reveals which products are picked up, which are returned, and where the customer goes after leaving the shelf. You can use this intelligence to create experiences that promote engagement with products and help shoppers learn more.

Retail sales revenue is a key performance metric, but in-depth analysis of poor sales performance is rare. By combining vision analytics with transaction data, you can gain insights into sales performance during periods of high and low traffic for each store.

Automated Inventory Management

Maintaining an accurate inventory is a major challenge for retailers. By connecting more parts of their operations and applying AI, retailers gain a comprehensive view of stores, shoppers, and products to help with inventory management.

Intel’s responsive retail technologies make it possible to collect and process information from sensors, cameras, and other sources. Designed to bridge islands of technology and eliminate data silos, this platform supports sensors and software from a variety of third parties.

Another type of AI inventory management uses smart shelves to quickly identify out-of-stock items and pricing errors. Inventory robots can alert staff to low stock or misplaced items for more-up-to-date inventories. And computer vision‒enabled checkout systems can help mitigate product loss in real time. As a result, retailers can run stores more efficiently and free up associates’ time to focus on improving the shopping experience.

Intel works with the retail ecosystem to deliver integrated, AI-powered solutions that solve real problems.

Intel® Technologies and Platforms for AI in Retail

Intel® technologies enable a number of exciting and emerging use cases for analytics and AI in retail:

  • Intelligent display ads use AI inferencing to understand customer engagement and interest. Content can be adapted to the audience in real time.
  • Smart shelves instantly check product availability so that items can be quickly replenished.
  • Endless aisle kiosks let customers see more products available at other locations. They also offer cross-selling and upselling opportunities.
  • Smart self-checkout systems accept loyalty cards, coupons, and transactions via mobile phone. Integrated video analytics identify products when a barcode is missing or unreadable.
  • A new class of retail solutions, like touchless kiosks that recognize speech and gestures and service robots that interact with customers, help shoppers minimize contact with people and objects.

At Intel, we work with innovators in the retail ecosystem to deliver integrated, AI-powered solutions that can be deployed quickly and cost-effectively. These partner solutions apply our wide range of AI capabilities, from computer vision at the edge to machine learning in the cloud. To find prevalidated solutions through Intel’s partner ecosystem, explore the Intel® Solutions Marketplace.

In addition, our Edge Insights for Retail platform brings together data from across your retail edge, setting the stage for hyperconvenient, engaging experiences and improved operations.

Intel® Technologies and Resources Power Artificial Intelligence in Retail

Edge Insights for Retail

Accelerate containerized deployments of computer vision and data-centric applications. By improving data accessibility and interoperability, you can create the in-store environment needed to deliver relevant customer experiences and better operational results. Find our latest offering of reference implementations for retail.

Intel® Movidius™ VPUs and Intel® Distribution of OpenVINO™ Toolkit

Intel hardware and software bring computer vision to automated checkout systems, smart shelves, inventory robots, and more. Intel® Movidius™ VPUs provide low-power acceleration for computer vision at the edge. The Intel® Distribution of OpenVINO™ toolkit streamlines the development of vision applications on Intel platforms, including VPUs and CPUs.1

Intel® RealSense™ Technology

Intel® RealSense™ technology enables vision‑based solutions designed to help you understand the retail environment in 3D.

Intel® Core™ Processors and Intel Atom® Processors

Intel® processors come in a range of options to give you the right level of performance where you need it. Ideal for retail solutions at the edge, including digital signage, robotics, POS systems, and interactive kiosks.

Intel vPro® Platform

The Intel vPro® platform delivers performance, built-in security features, and remote management capabilities to help ensure uptime for your critical retail devices.

Intel® Xeon® Scalable Processors

Intel® Xeon® Scalable processors deliver high performance for machine learning and deep learning in the cloud with built-in features to accelerate AI. This gives you a strong foundation for demand forecasting, predictive analytics, product recommendations, and more.

Intel® Optane™ Persistent Memory and SSDs

Intel® Optane™ persistent memory and solid state drives (SSDs) support large in-memory applications, ideal for retail AI workloads.

AI Software Tools

For developers, Intel offers software libraries and optimizations for popular frameworks like TensorFlow and Caffe to boost performance on Intel® architecture.1

In addition, Intel is leading the Open Retail Initiative (ORI) to encourage an ecosystem of interchangeable components and accessible retail solutions. Our goal is to accelerate the deployment of retail solutions through a common, open framework and make it easier for retailers to use AI and analytics.

Retail Thrives on AI

By adding AI capabilities to both the edge and the cloud, Intel and our partner ecosystem are helping retailers turn their data into powerful new insights. These data-centric solutions result in highly personalized experiences and product recommendations, accurate forecasts, inventory efficiencies, and smarter business overall.

Notices and Disclaimers

Intel® technologies may require enabled hardware, software, or service activation.

No product or component can be absolutely secure.

Your costs and results may vary.

Product and Performance Information

1Intel compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel® microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel® microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel® microprocessors. Please refer to the applicable product user and reference guides for more information regarding the specific instruction sets covered by this notice.