Zhurylo Victoria, PhD (Economics), Associate Professor of Marketing and Business Administration Department, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine

ORCID: 0000-0002-9533-1923
e-mail: vikroriazhurilo@knu.ua

Derbenova Yana, PhD (Economics), Associate Professor of Marketing and Business Administration Department, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine

ORCID: 0000-0003-1369-9888
e-mail: yana.derbenova@knu.ua

Typology of Consumer Behavior in the Context of using Artificial Intelligence in Purchasing Decisions

Abstract. Introduction. The rapid development of artificial intelligence (AI) and its integration into purchasing processes are transforming traditional patterns of consumer behavior and decision-making. The increasing use of AI-based tools changes the role of consumers in the purchasing process, particularly in terms of autonomy, trust, perceived risks, and motivation. At the same time, the lack of a comprehensive classification of consumers according to their interaction with AI limits the possibilities for effective market segmentation and the development of targeted marketing strategies.

PurposeThe purpose of the study is to develop a comprehensive typology of consumers who use artificial intelligence in purchasing decisions based on the integration of key behavioral and psychological characteristics. The study focuses on identifying the factors that differentiate consumer groups and determining their significance for understanding AI-assisted purchasing behavior.

Results. The methodological framework combines primary data collection through a consumer survey with methods of analysis, synthesis, and modeling. Consumer behavior was examined according to four key criteria: the level of trust in AI, intensity of AI use, perceived risks, and dominant motivational factors. Based on the identified relationships between these characteristics, consumer types were differentiated according to their patterns of interaction with AI during the purchasing process. The results demonstrate that the balance between trust in AI and perceived risks represents the principal factor differentiating consumer behavior. The proposed typology reflects differences in consumers’ behavioral and psychological responses to AI-based recommendations and provides a basis for more precise market segmentation.

Conclusions. The developed typology provides a conceptual basis for understanding heterogeneous consumer behavior in the context of AI-assisted purchasing decisions. Its application enables businesses to identify consumer-specific behavioral patterns and adapt marketing strategies, communication approaches, and personalization practices accordingly. The findings contribute to the development of customer-oriented marketing strategies by linking consumer characteristics with differentiated approaches to AI-enabled interactions.

Keywords: Consumer Behavior; Typology of Consumer Behavior; Market Segmentation; Digital Marketing; Artificial Intelligence; Marketing Personalization

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