Artificial intelligence (AI) is reinventing the retail landscape. Computer vision is enabling frictionless checkout and enhancing loss prevention for brick-and-mortar stores. Machine learning is streamlining inventory management practices. Conversational AI is shortening wait times and accelerating drive-through ordering at fast food restaurants across the globe. Retailers that harness AI to connect with customers and operate more efficiently will be better positioned to thrive in today’s AI-powered world.
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The Role of AI in Retail
Nearly all industries are feeling the impact of AI as it evolves and permeates all aspects of business.
Today’s retailers are using AI technologies in a variety of ways—from personalizing and enhancing the customer experience to creating a frictionless shopping journey to boosting loss prevention efforts.
Rotkäppchen-Mumm, the largest producer of sparkling wine in Germany, is one such retailer using AI to elevate the shopping experience. This winery runs real-time dynamic promotional content on digital signs in its stores. The sign content syncs with sales data and retail analytics to ensure a specific product won’t be advertised on screen if it is out of stock or low in inventory. Rotkäppchen-Mumm also uses these digital signs paired with near-field object recognition, RFID tags, and near invisible sensors to automatically display interactive content about bottles of wine placed near the screen.
Retailers are also exploring ways AI can help streamline their internal processes, assist employees in repetitive tasks, and unlock new insights for data-driven decision-making. For example, when Lee’s Famous Recipe Chicken faced a staffing shortage and wanted to improve its drive-through experience, it turned to a conversational AI-based attendant to greet customers, take orders, and upsell new items. This technology transition resulted in happier customers and a 95 percent order accuracy rate.1
Increasingly, retail businesses are looking at how more-complex types of AI, such as computer vision, deep learning, or generative AI, can help them anticipate and respond to customer needs better, as well as differentiate their brand in crowded and competitive spaces.
Create Frictionless Shopping and Checkout
Whether it’s a small boutique or a multinational superstore, retailers work hard to create shopping experiences that are convenient, personalized, and enjoyable. However, these shopping experiences are no longer enough to satisfy today’s tech-savvy, on-the-go customers. These customers now seek out frictionless shopping and checkout experiences—where most, if not all, interactions with the retailer are streamlined via technologies like AI, computer vision, deep learning, sensors, and software solutions to make the shopping journey as seamless as possible. By automating most of the transactional interactions, employees can focus on helping customers and other high-value tasks.
Nourish + Bloom grocery, the first autonomous grocery store in the Southern US, is an example of a truly AI-powered, frictionless, and contactless shopping experience. This store is designed for customers to shop with no checkout lines and no cashiers. To shop, customers download the store’s app, scan their phone when entering the store, load groceries into their cart, and walk out. The frictionless experience is powered by a combination of AI technologies, including:
- Thirty ceiling-mounted Intel® RealSense™ cameras used in combination with weighted store shelves that track what customers pick up.
- Intel® Core™ processors that process computer vision workloads and on-site analytics.
Watch this video for an inside look at the Intel® AI technology that makes frictionless shopping at Nourish + Bloom possible.
Provide Unforgettable, Personalized Customer Experiences
In addition to seeking out frictionless shopping, customers desire experiences that are tailored to their preferences. For retailers, that means personalizing shopping with AI. Digital signage embedded with computer vision can boost customer engagement and serve up real-time advertising that speaks to a particular audience. It can also be used to collect data about which types of customers are shopping and when. This information can be used, for example, by merchandising teams to make better decisions about product promotions.
Personalization can also be enabled through point of sale (POS) systems that can capture data about what was purchased and use that information to generate new product recommendations for each customer. Personalization also benefits retailers. Capturing and analyzing all this data leads to more-accurate segmentation and experiences that are tailored to a customer’s patterns and preferences, which in turn can help build brand loyalty, improve customer retention, and grow revenue.
Enhance Loss Prevention Efforts
Product loss and theft—also known as retail shrink—is a rapidly growing challenge for today’s retailers. In 2021, retail shrink cost United States-based retailers nearly USD 100 billion.2 By integrating AI, retailers can leverage object detection, motion analytics at the self-checkout station, and digital sensors to support loss prevention. When used with computer vision, these checkout systems can help mitigate product loss in near-real time.
Improve and Automate 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-enabled 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. As a result, retailers can run stores more efficiently and free up associates’ time to focus on improving the shopping experience.
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.
AI at the retail edge can 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.
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.
Intel® Technologies for AI in Retail
Intel offers a deep portfolio of flexible AI hardware technologies and optimized AI software solutions to help you more easily develop and deploy AI at your store, hotel, or restaurant.
| Intel® Technologies and Resources for AI in Retail | |
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Intel® AI Hardware |
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Intel® processors come in a range of options to give you the right level of performance where you need it. These CPU offerings are ideal for retail solutions at the edge, including digital signage, robotics, POS systems, and interactive kiosks. |
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Intel® Xeon® Scalable processors deliver high performance for machine learning and deep learning in the cloud, data center, or at the edge, with built-in features to accelerate AI. This gives you a strong foundation for demand forecasting, predictive analytics, product recommendations, and more—without the need to purchase additional GPUs. |
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Intel® discrete GPUs: Intel® Data Center GPU Flex Series and Intel® Arc™ graphics solutions |
Intel® discrete GPUs are designed to complement your Intel® processors so you can more efficiently handle increasingly diverse and complex AI workloads such as multiple object detection or multiple classification models. |
Intel® RealSense™ technology enables vision‑based solutions designed to help you understand the retail environment in 3D. |
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Intel vPro® Platform for retail with Intel® Active Management Technology (Intel® AMT) |
The Intel vPro® platform delivers performance and built-in security features and remote management capabilities with Intel® AMT to help ensure uptime and access to your critical retail devices, even if they’re outside your firewall or powered down. |
| Intel® AI Software | |
The Intel® Distribution of OpenVINO™ toolkit streamlines the development of vision applications on Intel® platforms, including VPUs and CPUs.3 |
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The Intel® Geti™ software platform allows you to rapidly develop powerful computer vision AI solutions to help you make data-driven decisions based on key visual data from your store, restaurant, or hotel. |
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| The Intel® oneAPI unified programming model | Intel® oneAPI is an open, free, and standards-based programming system that provides portability and performance across accelerators and generations of hardware to help streamline the development and deployment of AI models. |
| Developer resources for AI in retail | Our hub for retail AI developer resources offers reference implementations, code samples, kits, tools, and trainings for developers working on the latest retail innovations. |
Intel® Partner Platforms and Solutions for AI in Retail
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 our partner ecosystem, explore the following emerging use case solutions or visit the Intel® Partner Showcase.
- Intelligent digital signage ads use AI inferencing to understand customer engagement and interest. The platform adapts content to the audience in near-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 enable cross-selling and upselling opportunities.
- Smart self-checkout systems accept loyalty cards, coupons, and transactions via mobile phone or through touchless technologies. Integrated video analytics identify products when a barcode is missing or unreadable.
- Digital and touchless kiosks recognize speech and gestures and allow for hyperconvenient checkout options, self-service wayfinding, or in-store product research.
- Autonomous mobile service robots interact with customers and perform simple tasks to enhance the shopping experience.
Retail Thrives on AI
AI in retail opens up a world of new possibilities and opportunities for businesses to authentically connect with their customers, turn their data into powerful new insights, and take operations to the next level. Intel, alongside our partners, is here to help you bring your AI in retail ideas to life.