AI-POWERED PRICE OPTIMIZATION IN E-COMMERCE: ENHANCING COMPETITIVENESS AND PROFITABILITY

Abstract

Price optimization is essential for the success of e-commerce, especially in highly competitive markets. Artificial intelligence (AI) and machine learning (ML) have revolutionized pricing strategies, enabling the analysis of large volumes of data and the implementation of dynamic pricing that adjusts in real-time based on factors such as competition, demand, and consumer behavior. Personalization is one of the key benefits of AI-based pricing, allowing for customer segmentation and tailored offers for different consumer profiles. Additionally, AI facilitates competitive analysis by continuously monitoring market prices for strategic adjustments. This is particularly useful in saturated sectors, where small price variations can significantly impact customer acquisition and retention. Recent studies demonstrate the practical applications of these technologies. Cheng and Zhang (2024) developed an intelligent pricing model for international e-commerce, while Nathalie et al. (2024) explored AI’s impact on operational efficiency and strategic decision-making. Other studies highlight how AI improves consumer engagement and personalizes interactions. Despite the benefits, challenges such as robust infrastructure, ethical concerns (price discrimination), and data privacy require attention. Businesses must ensure transparency and regulatory compliance to prevent negative impacts. AI-powered price optimization represents a significant competitive advantage, driving profitability and enhancing the consumer experience. However, its adoption must balance innovation and ethical responsibility to ensure a positive and sustainable impact on e-commerce.