Neural network and customer experience. How to use AI in retail

According to expert forecasts, the global AI market in retail will reach $38.92 billion by 2029, and already about 40% of retailers use neural networks to solve their business tasks. Algorithms can analyze data in real time — identify behavioral patterns and offer personalized recommendations and optimal pricing strategies, which helps increase profits and competitiveness and optimize business processes. The use of artificial intelligence in retail opens new horizons for business, offers innovative approaches to interacting with customers and optimizing internal processes. In a rapidly changing market, companies using the power of AI have every chance to take leading positions.

1. ⁠AI can probably help with everything: from implementation of chatbots that will solve problems encountered by users instead of humans, to analysis of sales data, seasonality of purchases, and demand forecasting. But what are the limitations when implementing AI in retail?
2. ⁠Personalization at a new level. How can using neural networks for customer behavior analysis lead to creation of fully personalized stores?
3. AI and emotional intelligence. Can neural networks learn to recognize customers’ emotions and respond to them? What prospects and challenges does introduction of emotionally intelligent systems in retail bring?
4. How far can such technologies go in creating a human-like shopping experience?
5. How to maintain a balance between the customer’s and business’s interests?