Abstract

The swift progression of artificial intelligence (AI) technologies has significantly impacted various industries, with e-commerce platforms standing out as key beneficiaries. This paper delves into how AI enhances e-service quality on these platforms, emphasizing contemporary applications and emerging trends. AI driven tools such as chatbots, personalized recommendation systems, and predictive analytics have enabled e-commerce platforms to deliver more tailored, efficient, and satisfactory customer experiences. AI chatbots, utilizing natural language processing (NLP) and machine learning (ML), offer instant, round the-clock customer support, effectively resolving queries with minimal human intervention. Personalized recommendation systems employ sophisticated algorithms to analyse user behaviour and preferences, resulting in highly engaging product suggestions that drive customer engagement and increase sales. Furthermore, predictive analytics allow e-commerce platforms to forecast market trends, optimize inventory management, and tailor marketing strategies, thereby improving operational efficiency and customer satisfaction. This paper also examines the challenges of AI implementation, such as data privacy issues, the need for significant initial investments, and the necessity for ongoing technological updates. Through a thorough analysis of current AI applications and a review of recent scholarly works, this paper aims to underscore the transformative effects of AI on e-commerce service quality and provide insights into future advancements in this evolving field.

Keywords: Artificial intelligence, Electronic commerce, E-commerce, Sales, Learning systems, Machine learning, Big data