The Matrix of Influence: Generative AI Digital Nudging
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Digital nudging—using design elements in digital environments to guide user behavior—has become a critical tool across various domains, including e-commerce, health, and education(Weinmann et al., 2016). Current digital nudges tend to be predefined, relying on predefined triggers and actions, which can limit their flexibility, diminish their effectiveness, and require significant effort to construct (Gupta et al., 2024). With the recent advancements of Artificial Intelligence, particularly with Generative AI (GAI), there is an exciting opportunity to create more personalized, dynamic, and context-sensitive nudges. This study explores how GAI, enhanced by Natural Language Processing (NLP) and Machine Learning (ML) techniques, can be used to generate digital nudges that are no longer a part of a predefined set and can adjust to user behavior in real time. Unlike current approaches, GAI can enable the generation of personalized nudges that are not confined to manually set rules, allowing for greater adaptability and responsiveness to individual user contexts. By employing ML to understand user preferences and NLP techniques to refine text-content of these nudges, the study aims to develop a dynamic generative AI-driven nudging system capable of significantly enhancing user engagement and decision-making. This research holds the potential to bridge the gap between AI-driven personalization and practical applications in Information Systems. Moreover, further understanding the ethical considerations and innovation into generative digital user experience design. The findings can shed light on GAI and nudging systems to those interested in the intersection of AI, humancomputer interaction, and behavioral economics.