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AI in Retail – How Are New Technologies Transforming the Shopping Experience

Artificial intelligence solutions are transforming the retail industry. From empowering recommendation and personalization efforts with machine learning to optimizing delivery routes, the possibilities of using AI in retail are endless.

In this article, we’ll focus on the three main benefits of using AI in retail (improved customer experience, lowering costs, and data-driven decision-making) and give an overview of real-life use cases.

A promotion banner showing two people with a hologram clothes doll. It leads to a blog article about the use of AI in the retail industry.

With Chat GPT dominating the headlines, we are becoming more aware of how AI technology will soon touch every corner of our lives. From Netflix recommendations to global TikTok virality – even now, we can see how these algorithms will influence the way future generations experience the world.  

In business, data-driven organizations are set to dominate the landscape, and the retail industry is no exception. Advances in artificial intelligence and machine learning are already fueling significant change. Still, the true retail revolution is just around the corner.  

In this article, we’ll cover: 

AI in the Retail Industry 

Before we jump into the core topic of using AI in retail, let’s quickly go over the basics of artificial intelligence and machine learning.  

Artificial intelligence (AI) is a fast-growing area of computer science that uses machines and advanced datasets to simulate human thinking and actions. Machine learning (ML) is a subset of AI that focuses on developing systems that can learn over time based on the data they are fed. 

Artificial intelligence and machine learning solutions help retailers compile, process, and act upon vast amounts of data in real time.  

From cashless stores and robot assistants to fully automated delivery drones – these technologies are driving cutting-edge innovation and transforming the retail industry.  

For example, retailers can now leverage ML and AI technologies to better understand customers and market trends in order to forecast retail trends or provide a tailored shopping experience.  

So, it’s no wonder that according to a recent report, the global AI in retail market size will reach $24.1 billion by 2028.  

Benefits of AI in Retail 

AI technology has been around for a while, but we are just now starting to see its full effects – and the retail industry has been leading the charge.  

The main benefits of AI in retail are improved customer experience, reduced costs, and data-driven decision-making.

In this section, we’ll briefly cover each and explain how they’ll shape the retail industry.

Improved Customer Experience 

Today, you need more than a great product to stay ahead of the competition. To secure brand recognition and customer loyalty, you must provide a great customer experience. And to make things more complicated, customers are using more channels than ever to interact with a business. 

This is why AI and machine learning are invaluable for retailers who want to stand out.  

These technologies help you understand your customers by analyzing real-time demographic data, past purchases, and even their values and interests. These insights allow you to personalize your offer for each customer and avoid overwhelming them with irrelevant products or services.  

Another way retailers use AI technologies is through chatbots. Chatbots allow customers to get product information and connect with a brand without waiting. Automating responses to repetitive inquiries frees up your agents’ time – letting them focus on complex tasks that bring high value or high risk.   

However, retailers need to be careful when adopting new customer-facing AI technology. Otherwise, they risk poor implementation or unethical application that could hurt the brand long-term (after all, we all remember Microsoft’s AI chatbot Tay which turned into a hate machine just hours after being released to the public). 

Reduced Costs

Advances in artificial intelligence affect retailer profits not only by driving sales but also by lowering costs. So, it’s not surprising that – according to Accenture – AI has the potential to boost profitability rates by an average of 38% by 2035 and drive an economic boost of $14 trillion across 16 industries.  

By taking over mundane tasks and decreasing the necessary human input, AI allows your people to spend their time wisely and focus on tasks that genuinely matter and promote business success and customer satisfaction.  

For example, retailers can now use machine learning algorithms to optimize their delivery routes or completely automate their inventory management, lowering the number of products they need to keep in stock at any given time.  

Data-Driven Decision-Making 

Retailers collect vast amounts of data every day, but due to its size, it isn’t easy to analyze it and extract value. However, with AI technologies, retailers can make data-driven decisions by generating real-time actionable insights – moving them toward more effective outcomes. 

You can now use machine learning algorithms to process, filter, and analyze data from multiple sources as it comes in, transforming your big data into smart data.  

In doing so, you can visualize the most likely outcomes of specific strategies, promotions, and initiatives, helping you predict and take advantage of market changes.  

AI Use Cases in Retail

Even though artificial intelligence is becoming widespread, many retailers still don’t understand the underlying technology or how they can use it to differentiate. That could discourage them from implementing AI solutions, running the risk of being left behind.  

Because of that, we think it’s crucial to dive deeper into AI’s real-life application. This is why we’re sharing examples of the most common AI use cases in retail: personalization, product search, AI-powered contact center, inventory and delivery management, and demand forecasting. 


Thanks to advanced machine learning algorithms, it’s never been easier to provide a personalized shopping experience. By analyzing your customers’ demographics and past behavior, AI solutions can recommend products and offer campaigns tailored to specific customers and their needs.  

For example, Google Cloud Retail Discovery solution includes a ‘Recommendations AI’ module which offers highly personalized product recommendations based on customers’ past purchases and behaviors, context, and a product’s overall popularity. 

Product Search 

With product search, your customers can easily find in-stock products that match their search criteria. This makes the online shopping experience much more convenient – crucial if you consider that 94% of shoppers abandon their purchase if they can’t easily find the product they’re looking for.  

‘Retail search’ is another Google Retail Discovery module we use with our customers. This module gives your digital commerce website the capabilities of native Google Search – making it easy to find products your customers want, even if they are unsure what exactly they are looking for.  

AI-powered Contact Center 

Modern contact centers are becoming increasingly complex as they need to engage with customers across channels but also offer tailored recommendations and tech support.  

Another Google Cloud solution – Google Cloud Contact Center AI – is a cloud-native solution that helps you automate routine conversations using conversational AI. The solution helps you to increase efficiency while providing a seamless transition between the chatbot and your live agents in case of more complex inquiries.  

Inventory and Delivery Management 

AI can be a powerful tool for a retailer thanks to its ability to optimize promotional planning, pricing, supply chain operations, or delivery routes. 

For example, once a customer orders a product online, an AI tool can select the optimal warehouse based on its location and stock, calculate the best delivery route, and then provide the customer with an approximate delivery time. This not only serves to cut costs but has great potential to greatly improve the customer experience.

Demand Forecasting 

Demand predictions are vital in understanding consumers’ willingness to buy specific items and products at a particular price and timeframe. Thanks to that, you can identify optimal prices for each stock-keeping unit (SKU), set accurate and achievable targets, and stock sufficient supplies to maximize your sales for peak periods such as Black Friday.  

Reinvent Your Retail Experience with the Power of Google Cloud Platform 

To summarize – AI can be a powerful tool for retailers, with benefits ranging from automating great customer experiences to giving you smart data on which to base your decisions.

However, before you can take advantage of advanced artificial intelligence solutions, you need to unify your data and remove any data silos present across your business.

Google Cloud BigQuery is a cloud-based data warehouse that gives you a unified view of your data. It has built-in machine-learning capabilities, making it an ideal first step in your data-driven journey.