How AI Is Revolutionizing Retail

Updated Jun 5, 2024 • 8 min read

AI-powered commerce is ushering in an exciting new reality in which vendors can streamline their stores, and customers can make better buying decisions.

From $5 billion in 2022 to over $55 billion in 2030 is the estimated growth of the value of AI services in the retail industry.

These predictions are nothing out of the ordinary when you consider the many benefits that AI brings. It can effortlessly analyze customer sentiment at scale, identify trends that humans wouldn’t notice, personalize content for each customer individually, predict demand, provide customer support, and much more.

To thrive in the AI world, retailers are quickly modernizing their legacy infrastructure, adopting data security and privacy procedures, and balancing budgets to make room for AI. As more companies overcome these issues, AI solutions will proliferate across the whole industry.

What can AI do for retail?

Optimize store layout

AI enables retailers to find optimal store layouts, like the Fortune 50 home improvement chain Lowe’s did by combining technology from NVIDIA with AI to visualize different store arrangements.

The goal of this innovation was to enhance service, optimize operations, and promote collaboration. They created digital twins of several stores, which allowed them to run hundreds of AI-powered simulations to see how changes in the store would influence buyers.

This process is a much leaner substitute for the old-school way of building physical displays and putting them in front of real customers to analyze their reactions.

It also enables ecommerce-like capabilities for brick-and-mortar retailers. With sales performance and customer traffic data in simulations, stores can optimize the in-store experience more precisely than ever before.

Personalize every customer touchpoint

AI is a beast when it comes to personalization. From Netflix to Twitter, all major digital platforms use AI to personalize your experience to some degree. It’s gradually spreading across the retail industry as well, with capabilities such as:

Personalized product recommendations – based on a customer’s shopping data, an AI model can predict what they’re most likely to buy next, and deliver them a personalized offer through a notification, email, or pop-up at any step in the buyer’s journey.
Natural language search (NLS) – with NLS implemented in a store, shopping becomes less of a chore, and more like interacting with a store assistant. Customers can give a vague description of what they need instead of the exact keywords needed to find an item, and the AI will understand the intent and suggest appropriate options.

Assist customers while shopping

Virtual shopping assistants are streamlining the retail experience both online and in physical stores. When implemented properly, they can enrich the buyer’s journey from product discovery to post-purchase support.

They don’t just answer questions and find products, but also provide valuable insights into customer behavior. AI-powered virtual assistants can take the form of:

Chatbots – in the post-ChatGPT era, structured, tree-based chatbots are basically obsolete. AI-powered chatbots that understand the customer’s intent and can carry on a conversation are the new standard.
Assistants – a proactive version of a chatbot which doesn’t wait for the customer to ask a question, and instead reaches out to suggest better product alternatives, special offers, or help with picking the right size.

An interesting example of this is Walmart’s Text to Shop feature. Without any browsing, customers can just text one word to the service and it will return a few alternatives to pick from, or add to cart something that’s been ordered before. It also handles every stage of the buyer’s journey, from picking products to scheduling pickup times and checking out.

Predict trends and analyze customer sentiment

Whether it’s shopping histories or customer reviews, a thriving store can generate lots of data. To extract actionable insights from it without AI support would have been a grueling task.

Luckily, artificial helpers can chomp through troves of data like it’s nothing, and output accurate suggestions to improve your store thanks to capabilities such as:

Predictive analytics – analyze historical data to predict buying patterns, identify risks of customer attrition, and find ways to increase sales.
Sentiment analysis – uncover emotions from reviews to understand what your customers want the most.
Trend identification – stay on top of evolving customer preferences and be prepared for any rise or drop in demand for specific products.
Dynamic pricing – based on shopping data and competitor analysis, AI can identify optimal prices, continuously adjusting them in the store to ensure that they stay competitive.

Manage stock levels and minimize waste

Particularly useful for brick & mortar stores, even more so when they carry groceries, AI provides powerful capabilities to get your stock levels as close to customer demand as possible. An analysis from McKinsey & Co found that AI-powered forecasts can reduce supply chain errors by 50%, and reduce lost sales and product unavailability by 65%.

AI can help by:

Optimizing inventory management – to reduce risk of overstocking or stockouts, help allocate or replenish inventory, and reduce the need for seasonal markdowns.
Improving operational efficiency – to streamline supply chain and logistics operations, as well as optimize labor scheduling, delivery tracking, and route planning.
Reducing waste – to predict product expiration dates and optimize markdowns for perishable items.

A good example of this is US supermarket chain Cub, which was able to achieve an 18% decrease in produce waste thanks to an AI-powered solution called Afresh.

Detect theft and prevent fraud

Just in the US, retail shrinkage had cost the industry $100 billion in 2022. Shrinkage, that is loss of inventory caused by theft or administrative errors, is one of the biggest issues that retailers have to deal with. Cybersecurity breaches are a huge problem as well, with threat actors keen to exploit bugs in online stores to steal data or disrupt operations.

Both in physical locations and online, AI can help retailers detect and prevent criminal activity with:

Video and/or behavioral analytics – analyzing customer behavior in real-time, whether they’re browsing a physical or online store, can help detect suspicious activity quickly.

Inventory tracking – by tracking inventory levels and detecting discrepancies, AI provides better control over stock and helps minimize losses.
Exception reporting – analyzing transactions in real-time, AI can signal whenever irregularities happen, such as voids, refunds, or excessive discounts.
Scam prevention – AI can help detect popular scamming methods, such as phishing, to protect the store’s infrastructure from hackers.

Artificial intelligence, genuine returns

AI solutions won’t magically solve all problems that retailers face, but can still make a big positive impact on their financial and operational stability.

As the tech evolves, we’re bound to see more powerful AI retail solutions that will be cheaper and easier to implement. But there’s plenty to choose from already, so if you’re thinking about adding AI capabilities to your operations, reach out to our retail experts to get the ball rolling.