The use of AI in retail
The use of AI in retail has only begun, expert say. And few have missed the way AI has revolutionised several areas – such as in the healthcare industry and the auto industry. But is it possible also for retailers to utilise AI technology in their stores – without major investments or concerned customers? Moreover, which challenges and opportunities does AI in a retail setting entail? Learn more about the topic here!
AI has the potential to enhance the retailer’s business - and the shopping experience. But how?
What is AI?
Artificial Intelligence (AI) has several definitions, such as “the ability of a machine to display human-like capabilities such as reasoning, learning, planning and creativity” provided by the European Parliament, or "…technology that enables computers and machines to simulate human intelligence and problem-solving capabilities” by IBN. While the wordings can differ, most of the definitions highlight technology using human-related attributes. This means that AI can perform tasks that previously required human intervention – and perhaps even better or faster than humans were capable of.
As the technology is evolving rapidly, it has the potential to revolutionize many aspects of our lives – both personal and in a work-setting. But more concisely, how can retailers utilise this kind of technology already today?
How can AI be used in retail?
There are several areas where AI is already used, so also in the retail industry. However this is not yet common practice. As this type of technology is still fairly new, most retailers are yet to implement any AI solution, as many are curious yet somewhat cautious of this technology.
Here are some examples of how AI can be used by retailers – for various purposes.
Creating a personalized shopping experience
By using AI algorithms to analyze existing customer data, retailers can provide personalized product recommendations based on the individual customer.
For example, retailers like Amazon and Netflix use AI to suggest items based on past purchases and browsing behaviour, which increases customer satisfaction and sales. These personalized experiences are powered by machine learning models that continually refine their accuracy as more data is collected.
Of course, this could also be used in a physical store – as long as the retailers has sufficient customer data to make an informed decision.
Better or more efficient inventory management
AI has the possibility to help retailers manage their inventory more efficiently by predicting consumer demand and automating restocking processes. Furthermore, it can help retailers to avoid overstock or stockouts.
One example of this is Walmart, who uses AI to anticipate which products will be in demand and to optimize its supply chain, reducing overstock and stockouts . This predictive capability ensures that stores have the right products at the right time, enhancing customer satisfaction and operational efficiency.
AI-powered chatbots and customer service
AI-powered chatbots has perhaps become one of the first initiatives retailers and other B2C companies have implemented, with apparent benefits from the start. These systems provide 24/7 customer service, handling inquiries, processing orders, and troubleshooting issues.
These chatbots, utilized by companies like H&M and Sephora, improve customer engagement and free up human agents to handle more complex tasks. The natural language processing (NLP) capabilities of these chatbots allow them to understand and respond to a wide range of customer queries effectively.
Some concerns among both customers and researchers has been raised, pointing out that customers prefer actual human interaction when in need of help – however the chatbots and other ai-powered tool can act as a first-line support to handle standard enquiries.
The rise of visual search and virtual try-ons
AI brings the possibility to enhance the shopping experience with visual search and virtual try-on features. Search engines such as Google has recognized the need for visual search, where users can snap a photo of an item, and use it to find matching results.
Retailers like ASOS and IKEA also employ AI-driven visual search tools that allow customers to upload images and find similar products. Additionally, virtual try-on technologies enable customers to see how clothes or furniture will look on them or in their homes, reducing return rates and increasing buyer confidence.
The potential of dynamic pricing
AI algorithms can help retailers implement dynamic pricing strategies, adjusting prices in real-time based on factors such as demand, competition, and inventory levels. According to Boston Consulting Group, AI can help retailers translate their strategic choices for each product – and store. The technology is not only suitable for external changes – also internal changes can be managed using AI, ultimately affecting the pricing strategy.
Companies like Zara and Macy's already use AI to set optimal prices, with the goal of maximizing revenue and staying competitive in the market .
AI for fraud and theft detection
AI systems can be designed to monitor transactions for fraudulent activity, protecting retailers and customers alike. These systems analyze patterns and detect anomalies that may indicate fraud, allowing for swift action. Depending on the industry and the type of business, the indicators are different – the system use the data of the specific business to “learn” and detect anomalies or attempts of theft.
Retail giants like Target and Best Buy utilize AI for robust fraud detection, ensuring the security of online and in-store transactions. For retailers, shoplifting has been a common and recurring issue which AI tools aim to solve – in various ways such as video surveillance, anomaly detection or inventory management.
The challenges of AI for retailers
Of course, there are challenging elements when implementing AI for retailers, regardless of industry. As this kind of technology is still fairly new, there is much yet to discover, and the technology must be refined to suit the needs of the retailer.
One of the major challenges with AI that retailers have to overcome, according to Epicor, is the data quality and management. Not only is it a challenge to acquire enough data, but also to ensure that the quality of the data is sufficient for the AI solution to be effective. As the AI-solution will use the data to improve the outcome of the solution, there is a need for large amount of accurate and reliable data.
Another obstacle is the education regarding AI – not only how it works and how to utilise it, but also which solutions to choose from an ever-increasing variety of services. Retailers may struggle to find the suitable solution for their business’ specific needs, and fail to invest in the AI-solution that brings the most benefits. For example, should the retailer focus on improving internal processes and workflows such as inventory management, or invest in a solution that is more customer-oriented such as AI-powered product recommendations? This depends on the level of ambition, and where the retailer has the most to gain.
What about AI for grocery retailers?
Businesses in different industries have their own challenges to handle – and their own solutions to solve the problems. So how can grocery stores benefit from AI solutions as well? Contact us to learn more!
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