The Impact of Dark AI Patterns on Consumer Purchase Decisions and Impulsive Buying

Huber Gasinski, Barbara Szymoniuk, Magdalena Maciaszczyk, Maria Kocot, Janusz Sobon, Dominik Baldowski, Krzysztof Kandefer
European Research Studies Journal, Volume XXIX, Issue 1, 490-499, 2026
DOI: 10.35808/ersj/4324

Abstract:

Purpose: The purpose of this study is to examine the relationship between consumers’ susceptibility to artificial intelligence-based manipulative mechanisms (Dark AI Patterns) and the level of impulsive buying behavior in an e-commerce environment. Design/Methodology/Approach: The study employed a survey method conducted in 2025 among 429 online shoppers. Two composite indices were constructed to measure susceptibility to Dark AI Patterns and impulsive buying behavior. The relationships between variables were assessed using Pearson’s correlation coefficient. Findings: The results indicate a moderate level of both susceptibility to AI-based manipulation and impulsive buying, as well as a statistically significant positive relationship between these variables. Practical Implications: The findings highlight the need for responsible design of e-commerce systems and for limiting excessively persuasive algorithmic techniques in order to reduce the risk of uncontrolled purchasing decisions. Originality/Value: The study integrates research on impulsive buying with the analysis of the manipulative potential of artificial intelligence and provides empirical evidence demonstrating the interdependence between these phenomena.


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