How GenAI will support the transition from personalization to hyperpersonalization at scale

Generative Artificial Intelligence (GenAI) is evolving rapidly and is fundamentally reshaping how organizations design and deliver personalized digital experiences. By enabling real-time, context-aware, and individualized interactions, GenAI supports the transition from traditional personalization approaches to hyper-personalization at scale. However, despite these technological advances, many organizations continue to rely on static personalization practices, while digital customer journeys grow increasingly complex and dynamic. As AI-powered systems become more prevalent in digital customer interactions, it is critical to understand how GenAI contributes to this transformation. This research examines the role of GenAI in enabling the shift from personalization to hyper-personalization at scale and investigates the key factors influencing customer engagement with GenAI-driven digital tools. To achieve these objectives, a conceptual model was developed and empirically tested. The model incorporates five perceptual constructs derived from the existing literature: Trust in AI, Privacy Concerns, Perceived Value, Perceived Hyper-Personalization, and Sentiment-Adaptiveness. A mixed-methods research design was adopted. Quantitative data were collected through an online questionnaire distributed to adult users of digital services, while qualitative open-ended responses were used to complement the analysis. The empirical context focuses on the banking sector, selected due to its data-intensive operations and strict regulatory environment (N = 112). The quantitative analysis was conducted using multiple regression analysis and Partial Least Squares Structural Equation Modeling (PLS-SEM), while qualitative data were analyzed thematically. The findings indicate that Perceived Hyper-Personalization and Perceived Value are the strongest drivers of Customer Engagement, suggesting that users are more likely to engage with GenAI-powered services when interactions are perceived as highly relevant, personalized, and useful. Trust in AI exhibits a positive but weaker effect, functioning as a supporting factor, whereas Privacy Concerns act as a limiting condition. Sentiment-Adaptiveness does not directly influence engagement but contributes indirectly through its effect on perceived hyper-personalization. Overall, the study reveals a multi-layered engagement mechanism and provides a structured framework for the strategic design of GenAI-enabled hyper-personalization, particularly within digital banking environments.