Artificial intelligence has become a significant tool in e-commerce, particularly in product recommendation systems. Companies like Amazon and Alibaba use advanced algorithms to analyze customer behavior and preferences, providing personalized shopping experiences. This approach not only facilitates smoother transactions but also encourages repeat purchases. AI-driven recommendations significantly improve customer satisfaction and sales performance by tailoring suggestions based on individual user data. Techniques like fuzzy logic and genetic algorithms refine the accuracy of recommendations. AI also plays a crucial role in fraud detection, with machine learning approaches like Hidden Markov Models (HMM) and decision trees demonstrating superior performance in identifying fraudulent transactions. This proactive approach not only protects businesses from financial losses but also builds consumer trust. AI's role in optimizing pricing strategies is also noteworthy, with platforms utilizing dynamic pricing models that adjust prices based on real-time market data, competitor pricing, and consumer behavior. This adaptability maximizes profits and ensures competitive pricing in the fast-paced e-commerce environment. Artificial intelligence also enhances customer relationship management (CRM) by analysing customer data to predict behaviors and preferences. By analysing customer interactions and feedback, AI can identify trends and future behaviors, enabling targeted marketing campaigns. This personalized approach fosters stronger emotional connections between consumers and brands, ultimately driving loyalty and repeat purchases. There are also several approaches how it can enhance the development of e-commerce solution. For example, code generation, interface design or prototyping