The Role of Behavioral Conditioning in AI-driven Marketing Strategies: Quantitative Research

This research explores the role of behavioral conditioning in AI-driven marketing strategies. There is limited research on the extent to which classical and operant conditioning impact consumer autonomy. While AI enables hyper-personalized marketing, conditioning methods could improve associative learning and habit creation in consumers. This article is the third in a series of works that extend research and explore the intersection of conditioning and AI marketing. The authors conducted quantitative research. Using non-probability snowball and convenience sampling, 789 participants voluntarily participated in this research. Using SPSS 30, the descriptive, correlation, and regression analyses were conducted. Moreover, two theoretical frameworks, the Technology Acceptance Model (TAM) and Self-Determination Theory (SDT), were used to better understand the existing research gap. The survey results showed a significant correlation between AI-driven conditioning strategies and their impact on buyer behaviors, engagement rates, and brand loyalty. Moreover, the need for adaptive frameworks was identified to manage the integration of AI with classical and operant conditioning. Moreover, these results offer valuable insights into the academic discourse on human-AI integration in Marketing. Hence, the authors propose actionable insights for businesses to balance innovation and consumer trust in the AI era.