Transforming marketing strategies via AI-powered personalization: A systematic review of consumer experience and business strategy
The integration of artificial intelligence (AI) in marketing has allowed for highly personalized customer experiences, transforming the traditional engagement strategies (Davenport et al., 2020). However, the implications of this for consumer behavior, ethical standards, and business performance are fragmented in the literature. This systematic review synthesizes current research on AI-driven marketing personalization, followed by examining the underlying technologies, their impact on consumer and business outcomes, associated ethical concerns, and existing research gaps. In line with the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 (Page et al., 2021), we conducted a systematic search that included studies that were published between 2015 and 2025. The most popular AI tools used for personalization were recommendation systems, machine learning (ML) and natural language processing (NLP). It has been found that AI-powered personalization helps to boost customer satisfaction, engagement, and brand loyalty. The proposed AI-personalization-ethics model (AIPEM) is an abstraction of these results and a comprehensive model for understanding AI personalization in marketing. Future studies are needed in the direction of responsible AI design, validation of the AIPEM model in practice, and long-term evaluations of its impact on consumers.