AI in the retail market is expected to grow higher and higher with the growth from $4.84 billion in 2021 to $31.84 billion in 2028. However, not all companies understand and are ready to grasp the benefits of AI to boost their performance. Therefore, this article will introduce briefly the recent trends of AI, the advantages when adopting AI to business, and some telling use cases in the field of retail.
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Top 7 significant trends of AI in the retail
1. AI chatbot as a virtual customer service assistant
According to the Forbes (2020), 54% of online shoppers chose brands for several key reasons:
- 58% for speed in finding preferred items
- 76% for prioritize convenience in the shopping experience
- 44% for quality of customer service
- 42% for quick and straightforward checkout process
AI-powered chatbots can significantly enhance all of these aspects. By leveraging big data analytics and artificial intelligence, chatbots can swiftly analyze customer needs and insights, recommend products, answer product inquiries using extensive data from past transactions, and assist the sales team with pre-order requirements. A 2022 survey by Statista indicated that nearly 40% of American consumers have engaged with AI chatbots while shopping online, highlighting their growing popularity and the necessity for retail businesses to adopt them in the future.
2. AI in retail for demand forecasting and inventory optimization
In recent years, demand forecasting systems that integrate AI have garnered significant interest from companies. AI-powered demand forecasting, utilizing machine learning algorithms, offers several advantages over traditional systems. It can efficiently process vast amounts of data and perform analyses with high accuracy. According to McKinsey & Company (2022), AI-based demand forecasting can reduce errors in supply chain networks by up to 50% and decrease lost revenues from out-of-stock situations by 65%. By examining factors like customer behavior patterns, businesses can better understand the demand for individual items, optimize purchasing and inventory management, and strategize discount campaigns for sales promotions.
3. Supporting product display
An AI-driven product demand forecasting system aids in decision-making regarding product placement by accurately predicting purchase quantities and arrival times. This system often collaborates with robotic arms to assist in replenishing and displaying products, taking over tasks typically performed by humans. Additionally, it not only helps businesses reduce costs but also contributes to environmental sustainability by minimizing the number of discarded products.
4. Price optimization
With the process of machine learning algorithms and big data, AI technology can help companies leverage their pricing strategies by seeing how customers react to various price points of a product, analyzing competitors’ price ranges, and developing better discount campaigns.
For example, AI can analyze historical sales data to identify optimal pricing strategies based on customer behavior and preferences. By evaluating how customers respond to various price points, businesses can fine-tune their pricing models to maximize sales and profit margin.
5. Virtual fitting room
The virtual fitting room is a technology that has developed rapidly in recent years after successfully combining AI, VR (Virtual Reality) and AR (Augmented Reality). In the virtual fitting room, customers can see the image of themselves wearing their clothes without having to change too many clothes. It helps prevent returns while improving the customer experience. According to Fortune Business Insights (2025), the global virtual fitting room market size was valued at USD 4.79 billion in 2023 and is projected to grow from USD 5.71 billion in 2024 to USD 25.11 billion by 2032 The virtual fitting room market is projected to grow from $2.97 billion in 2021 to $8.5 billion in 2028.
6. Recommendation system powered by AI
R&D departments in retail companies can leverage AI to adopt new product designs. By analyzing vast amounts of data from various sources, AI aligns its recommendations with the company’s vision and goals. This ensures that the suggested designs are in harmony with the business’s sales strategy.
Additionally, recommendation systems can be integrated into e-commerce platforms. With an AI-powered recommendation engine, customers can input a few keywords describing the products they seek. AI then analyzes personal data from the user’s account, such as age, gender, search history, and past transactions, to provide tailored recommendations based on those keywords. The choices customers make help the AI learn more about their behavior, enabling the company to gain deeper insights into customer needs and preferences in e-commerce environments.
7. Data protection
Data is one of the invaluable assets of every company nowadays. A cyberattack is a true nightmare, especially for companies in the retail industry. However, AI technology could help businesses prevent risks as it can detect anomaly patterns in data sources in real time. By leveraging machine learning algorithms, businesses can monitor transactions and user behaviors in real-time, allowing them to respond swiftly to suspicious activities. This proactive approach not only mitigates risks but also builds customer trust, as consumers feel more secure knowing their data is protected
Conclusion
In conclusion, adopting cutting-edge technology like artificial intelligence (AI) in retail will help companies stay competitive. With Verysell AI, retail businesses can focus on their expertise with optimum AI solutions developed by our experienced IT experts. If you are looking for a solution to adapt AI into your business in the future, do not hesitate to contact us for more information.