AI in Retail: Use Cases and Examples

AI in retail isn’t new. In the early 2000s, Amazon introduced its groundbreaking recommendation engine, Walmart transformed inventory management, and Macy’s implemented dynamic price optimization—all with the help of AI.

While advancements in AI were gradual until 2022, the launch of ChatGPT marked a significant turning point, accelerating AI integration across the retail sector. Since then, we’ve witnessed AI technologies and AI tools enhancing nearly every facet of retail operations.

Retailers have swiftly embraced these innovations to boost customer engagement. A 2023 report by McKinsey reveals that the adoption of AI tools in retail has increased by 25% year over year since 2020, with no signs of slowing down.

This article will explore the future of AI in retail, provide recent examples, and discuss how AI benefits the industry as a whole.

Is AI the future of retail?

The recent surge in AI innovation has already transformed how retailers operate internally and interact with human customers. 

For example, AI-powered chatbots provide shoppers with instant assistance. Personalized recommendation systems like Netflix’s AI suggest products that match consumer preferences. And Amazon’s Just Walk Out technology eliminates traditional checkouts.

While retailers are adopting tools to improve operations and create convenient experiences for human customers, AI tools are moving the innovation needle for retail businesses one more notch forward. AI advancements also introduce a new kind of customer for retailers to cater to—the “machine customer.”

Machine customers are AI-driven entities that autonomously make transactions for consumers. For example, a smart refrigerator can order groceries, a home assistant can stock up on house supplies, and a smart printer can reorder ink when toner is low—all without any human consumer intervention.

Experts estimate that by 2028, 15 billion connected products could act as autonomous customers, optimizing demand-supply matching in real-time and reshaping supply chains, sales, and customer service. CEOs also predict that by 2030, 15% to 20% of their revenue will come from machine customers, influencing trillions of dollars in purchases.

So, is AI the future of retail? In a word, yes. It glimmers in the past. It’s ubiquitous in the present. And it’s most likely the entire future—not only from a retailer’s perspective but from consumers’ too.

Examples of AI in retail

While we haven’t quite reached the phase where robots run every aspect of retail, AI has already improved several critical, time-consuming operations. Here are some prime examples:

Demand forecasting

By analyzing historical sales data and market trends, AI can predict future product demand, helping retailers optimize stock levels and reduce waste. 

For example, Walmart leverages AI-driven demand forecasting to efficiently manage inventory across its global supply chain. According to McKinsey, AI-based demand forecasting can reduce inventory costs by 10% to 40%. Walmart reported saving billions of dollars annually through improved supply chain optimization, inventory management, and reduced waste.

Shopping recommendations

Retail AI enhances personalized shopping experiences by suggesting products based on customer data, boosting sales, and improving customer satisfaction.

If you’ve purchased something from Amazon recently, you’re familiar with Amazon’s recommendation engine. It offers product suggestions based on your browsing and purchasing system. Its AI uses complex algorithms to analyze patterns and predict which products you’re most likely to buy.

Frictionless checkout

AI technology enables seamless checkout experiences, removing the need for manual scanning or cashier interaction, thus speeding up the shopping process and reducing wait times.

For example, Amazon Go stores use AI to automatically detect when products are taken or returned to shelves and charge customers as they leave. This technology relies on a combination of computer vision, sensor fusion, and deep learning algorithms to track items and engage customers in real-time.

Automated inventory management

Real-time inventory monitoring is possible with AI, which automates restocking and reduces the chances of stockouts or overstock situations. Fast-fashion retailer Zara uses AI to track inventory and quickly replenish popular items. Specifically, Zara uses RFID (Radio Frequency Identification) tags to track inventory in its stores. 

These tags provide visibility into item-level locations, enabling Zara to quickly identify low stock levels and replenish items before they run out.

Sentiment analysis

Retailers can gauge public sentiment about products or brands through AI analysis of customer reviews and social media posts, informing decisions about product offerings and marketing strategies.

For example, makeup and skincare retailer Sephora uses AI to analyze customer feedback, which helps improve product recommendations and store layouts by identifying trends and preferences in large data volumes. 

Loss prevention

AI detects and prevents theft and fraud by monitoring in-store activity and identifying suspicious behavior, reducing losses. Drugstore chain Walgreens employs AI to analyze security footage and detect potential shoplifting incidents in real-time. 

This technology uses machine learning algorithms to monitor video feeds, identify suspicious behavior, and alert security personnel instantly. The system improves its accuracy over time by learning from past incidents.

How AI can benefit the retail industry

Now that we’ve looked at some concrete examples of AI working in the retail world, let’s talk about artificial intelligence and how it can benefit the industry:

More accurate inventory counts

AI technology eliminates human error by automating real-time inventory tracking and management. Machine learning algorithms analyze sales data, customer demand, and stock levels to ensure correct inventory levels and counts. The result? Reduced overstocking and stockouts.

For example, Target has successfully implemented an AI-driven inventory management system known as the Inventory Ledger. This system uses advanced machine learning models and IoT devices to provide accurate inventory data in real-time across 2,000 stores.

To quantify its effectiveness, the Inventory Ledger processes up to 360,000 inventory transactions per second and handles as many as 16,000 inventory position requests per second—a task only a machine could handle. 

Better shopper engagement

AI technology is also a win in terms of boosting shopper and customer engagement. Machine learning algorithms analyze customer data to offer tailored product suggestions, anticipate needs, and provide personalized promotions.

For example, Sephora uses AR and AI-driven tools like virtual try-ons and personalized skincare recommendations based on customer data and preferences. These tools make it easy for customers to select the right product for their unique skin type—without having to set foot in a store.

Improved customer service

With AI, it’s easier now than ever to cater to customer demands. AI technology can keep up with simultaneous customer support requests around the clock. AI automates responses, reduces (sometimes eliminates) wait times, and personalizes interactions.

For example, clothing and home goods retailer H&M recently implemented AI-driven customer service solutions to enhance its online and in-store experiences. Its virtual assistant manages customer queries related to product availability, order status, and return policies, providing quick and accurate responses. 

More targeted marketing campaigns

It makes sense why 91% of marketers already use AI as a companion in their jobs. AI is the King of Marketing Accuracy and Efficiency. 

It guides retail marketers in data-driven decision-making, revolutionizes marketing forecasting, and analyzes user data to create highly personalized and targeted campaigns. What’s more, AI completes these tasks in a fraction of the time.

Store assistance

AI also helps retailers improve their in-person and online stores by assisting with skill sets they might not possess. For example, Shopify offers retailers the help of its AI tool, Shopify Magic.

Shopify Magic helps you with tasks like generating and editing professional product photos, writing better product descriptions, improving email correspondence with customers, and turning live chats into sales opportunities.

Don’t get left behind

The 2024 AI retail stats are in, and they’re telling a clear story: AI isn’t only the future of retail—it’s the future of, well, everything. Full stop.

Stats show that generative AI alone has caught on faster with the public than smartphones or tablets.

Retailers who don’t want to be left behind are adopting AI to speed up, streamline, and improve everything across the supply chain—from manufacturing to marketing. Today, staying ahead in retail means keeping abreast of AI tools and trends. 

So, what’s the perfect place to start? How about with your Shopify store? Check out Shopify Magic to learn how it can help you create a more efficient retail business.