Many companies in the retail, supply chain and logistics industries have been thinking about how to integrate artificial intelligence into their processes – be it through automation, predictive analytics, machine learning or generative AI systems.

While some companies are already well advanced in certain areas, it is hard to deny that many companies’ strategies are already as advanced as the two titans of the industry: Amazon and Walmart.

Some of the methods by which the two giants try to outdo each other remain largely similar, but in some
In some cases, the giants take different approaches to developing and implementing their technologies.

Amazon: Summary of reviews

Amazon released more information earlier this year about how it uses artificial intelligence to create customer reviews, noting that the systems can detect whether a review may be fake.

The company also said it uses AI to aggregate reviews and create summaries. A spokesperson said these are designed to “help customers see common themes across dozens, hundreds, or even thousands of reviews at a glance to help them quickly understand customer insights.”

With AI features to assist customers, they are designed to make faster decisions while also receiving answers to frequently asked questions and accessing aggregated sentiment.

Amazon: AI for product discovery and search

Amazon announced Rufus, its generative AI shopping assistant, earlier this year. According to a spokesperson, “Rufus is trained using Amazon’s product catalog, customer reviews, community Q&A, and information from across the web to answer customer questions about a wide range of shopping needs.
and products, make comparisons and give recommendations based on the context of the conversation.”

The company also uses generative AI to help sellers write product descriptions that
resonates well with customers. The tool ensures that when a seller lists a new item, its title and descriptions attract consumers’ attention and answer their questions. Sellers can also enrich existing listings, making the discovery process easier for the consumer.

Amazon: Inventory Management

Amazon has a system called Supply Chain Optimization Technology (SCOT), which a spokesperson
described as “the central nervous system of Amazon operations.”

The spokesperson explained that the underlying systems behind SCOT enable the e-commerce giant to manage a supply chain with millions of sellers while
This allows these sellers to manage their inventory and stores themselves.

“There are actually many AI systems that work together and together make countless predictions and
decisions every day. SCOT transforms our huge data sets into predictive intelligence and tells us what inventory to buy, where to store it, how to select it and ship it. It both forecasts demand and coordinates warehouse operations. It’s like a master conductor leading an orchestra of millions,” said the spokesperson.
said Sourcing Journal.

Amazon: Warehouse automation

An Amazon spokesperson said that many of the company’s cutting-edge AI systems have already begun to prove their value and improve the customer experience, but that it is the company’s internal AI systems – some of which have been in use for many years – that will drive the broader change.

“Amazon has one of the most extensive networks in the history of commerce. We collect, pack, ship, sort and deliver billions of packages around the world every year. And we are constantly striving to get faster and offer our customers the widest selection of items at affordable prices. In today’s complex supply chain
“This is simply not possible in the supply chain without the most advanced AI systems in the world,” the spokesman said.

The company, the spokesperson said, uses more than 750,000 robots to fulfill orders. However, the spokesperson noted that even as its robot fleet expands, the company continues to add new roles to keep up with that growth.

For example, Amazon had to train some of its employees to become robot supervisors and technicians. Maintenance technicians were also hired to ensure the smooth operation of the fleets.

“By taking on strenuous or repetitive tasks, our robots help make our employees’ work safer,” the spokesman said.

Amazon: Last-mile optimization

For Amazon, last-mile optimization begins before the customer actually makes the purchase, a spokesperson said.

“Delivery optimization starts long before a customer places an order. In fact, we use AI to predict demand, inventory distribution (and) even the number of drivers we need more than three months before a customer clicks ‘buy now.’ This type of predictive intelligence requires two things: massive amounts of highly reliable data and powerful AI models to turn that data into insights,” the spokesperson said.

The company uses large language models (LLMs), neural networks and ML to ensure drivers can take the safest routes while remaining efficient. The systems it trains take into account weather forecasts, driver feedback, historical data and more

And by using generative artificial intelligence, the spokesperson said, drivers could navigate large office parks, apartment complexes and confusing terrain more quickly – based on what the systems can know and understand about the locations in question.

“In many countries, such as India and Japan, street addresses do not follow a standardized format. Some places are described informally: ‘third house on the right after the barn,’ for example. Using generative AI, we can derive precise map locations from non-standard addresses. This makes it easier and faster for drivers to find specific places,” they said.

Walmart: Summary of reviews and product comparisons

Jon Alferness, Walmart’s chief product officer, shared on his LinkedIn account in May that Walmart is using generative AI for product and review summaries.

Instead of reading all the specifications of a product or going through dozens of reviews,
can use the AI-powered summaries as a starting point.

“These new tools capture the essence of customer sentiment on the most discussed product aspects across thousands of text reviews, enabling customers to quickly understand overall sentiment and make more informed decisions,” Alferness wrote.

If the customer has a question that is not answered in the summary, they can dive deeper into each individual feature of the product.

Alferness announced on LinkedIn in April that the company had also used AI in its app to give customers the ability to compare up to four similar products by features, price, reviews, fulfillment options and more.

Walmart: Generative AI for search

The Bentonville-based Big Dog announced earlier this year that it would launch a generative, AI-powered search tool that would allow customers to quickly find and order products through its iOS app.

Traditional search requires the user to type in a specific product or brand. However, Walmart’s generative AI search feature allows the user to ask questions like, “Help me plan a disco-themed birthday party.”
“Show me what to wear to a wedding.” or “What do I need to host a Super Bowl party in my apartment?”

According to the company, the tool can also take into account location, search history and other contextual information about each user to provide personalized results to customers who use the feature. The company expects the feature to provide a more efficient and convenient experience for in-app shoppers.

Walmart has launched its new search feature using its own data combined with LLMs and technology from Microsoft. The company plans to expand the generative AI-powered search to Android and its website later this year.

According to a June press release, the company is also beta testing a conversational chatbot designed to make product discovery easier.

Walmart: Inventory Management

Walmart said it uses ML and AI-powered inventory management to ensure products arrive at the right place at the right time and in the right quantity. The company has been highlighting the technology especially during the 2023 holiday season.

The company uses its historical sales data as well as engagement metrics like e-commerce searches and page views, paired with third-party data like climate and weather patterns, local trends, demographics of specific locations, and more. Once these inputs are fed into the model, it can help predict the type of demand that will be associated with certain products, both during the holiday season and throughout the year.

“By the time our customers are ready to shop, our AI/ML data has already done the heavy lifting of improving warehouse flow,” wrote Parvez Musani, senior vice president of end-to-end fulfillment, in a blog post in December.

Walmart: Warehouse automation

In April, Walmart announced plans to introduce 19 autonomous forklifts into four of its high-tech distribution centers in partnership with Fox Robotics.

The forklifts unload the pallets and take them to an area where another automated system can catalog and sort the pallets’ contents. The company said distribution center employees would help determine the optimal method for unloading the pallets, even if they no longer have to do so manually.

“I see players becoming coaches and I am incredibly impressed,” wrote Maurice Gray, general manager of the distribution center where the FoxBot forklifts were first tested, in a Walmart blog post.

Walmart: Optimizing the middle mile

Walmart released its proprietary AI-powered route optimization software to other companies in April, with the goal of simplifying problems in the middle mile of the supply chain.

The technology takes into account traffic conditions, customer locations, delivery times and more to show drivers the most efficient routes for pickup and delivery. The company said it is also reducing its carbon footprint as a result. Since the beginning of this year, it has eliminated about 30 million unnecessary miles and reduced its footprint by about 94 million pounds of carbon dioxide.

Emily Schmid, senior director of channels and platforms and digital strategy at Walmart, said route optimization has helped put products directly on consumers’ paths, reducing inefficiencies in the supply chain.

“With its ability to intelligently organize and manage loading, route optimization has made our employees’ jobs more efficient,” Schmid told Sourcing Journal earlier this year. “It has improved our drivers’ experience by eliminating unnecessary wait times during their trips… Our main goal is to save people money so they can live better; today that applies not only to our customers but also to other companies and the communities we serve.”