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Artificial intelligence (AI) has emerged as a revolutionary and transformative force across multiple spheres of life, notably reshaping industries with marketing as a prime beneficiary, enabling it to multiply sources of information and data, improve software data management capabilities, and design complex and advanced algorithms. The integration of artificial intelligence into marketing strategies is radically transforming the way companies engage with their customers. By personalizing the customer experience, AI makes it possible to offer more tailored and responsive services, with a positive impact on customer satisfaction and loyalty. Moreover, AI has demonstrated its ability to enhance decision-making processes, optimize resource allocation, and create new opportunities for competitive advantage within dynamic market environments. Our systematic literature review, based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, analyzed 195 potentially relevant articles on the subject from four databases (Scopus, Science Direct, springer and web of Science). After applying the inclusion and exclusion criteria, 24 articles were selected for detailed analysis. The primary findings of this review indicate that the application of artificial intelligence to personalize the customer experience leads to significant improvements in terms of customer satisfaction and operational efficiency. Nevertheless, personalization, as a significant notion, remains relatively unexplored in artificial intelligence research and practice. AI technologies such as deep learning, predictive analytics and interactive chatbots were frequently cited as catalysts for better understanding and anticipating customer needs. However, the studies also highlight significant challenges, particularly in terms of data security, ethical considerations, transparency issues and maintaining human engagement in customer interactions. Implications for research and directions for future research in the field of marketing and artificial intelligence were suggested.
Timimi et al. (Sun,) studied this question.