From Prediction to Personalisation: How Artificial Intelligence Is Transforming Marketing Strategies

Artificial intelligence (AI) has moved from a peripheral tool to a structural component of contemporary marketing strategy, promising unparalleled efficiency in demand forecasting, audience segmentation, and the delivery of individualised customer experiences. Yet the gap between what predictive analytics enables technically and what organisations achieve relationally remains poorly understood. This study adopts a qualitative, interpretive design to investigate three interrelated questions: 1) how predictive tools practically inform strategic decision-making in contemporary campaigns; 2) through what processes predictive insights translate or fail to translate into meaningfully personal customer experiences; and 3) which organisational, ethical, and creative factors enable or constrain genuine transformation. Data were collected through 24 in-depth, semi-structured interviews with senior marketing practitioners across e-commerce, consumer packaged goods, financial services, and technology sectors in the United States between January and June 2026. Reflexive thematic analysis, anchored in Huang and Rust’s [1] multi-intelligence framework, revealed that predictive analytics has become infrastructural, driving real-time budget reallocation (83% of participants and dynamic audience segmentation (75%), yet the translation to felt personalisation is fragile. While 67% reported successful dynamic adaptation, 79% described over-personalisation failures, and 88% identified ethical constraints as the most consequential obstacle. Cross-functional collaboration and retained creative agency emerged as decisive enabling conditions. The findings extend prior theory by demonstrating that progression from thinking AI to feeling AI is not automatic but requires deliberate organisational mediation. Implications for practitioners, scholars, and policy-makers are discussed.