Rohden, Simoni FernandaBelchior, Maria Beatriz Gonçalves2025-11-062025-10-27http://hdl.handle.net/10362/190187Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing IntelligenceThis study investigates the impact of AI-based recommendation systems on consumer behavior in B2B retail environments, with a specific focus on satisfaction and purchase intention. As artificial intelligence becomes increasingly integrated into business decisionmaking, understanding its perceived value compared to traditional sales approaches is essential. The study was conducted through a survey of 155 respondents from a local food retail chain in Portugal, including franchisees and central structure employees. Using a conceptual framework supported by established theories of trust, personalization and technology adoption, the study tested the direct influence of AI-based recommendations on satisfaction and purchase intention, as well as the mediating roles of perceived trustworthiness, competence and personalization. A moderation analysis was also conducted to assess the impact of buyer experience on these relationships. The results indicate that AIbased recommendations significantly increase satisfaction and purchase intention, with strong mediating effects of the identified trust-related variables. However, buyer experience did not significantly moderate these effects. These findings contribute to the theoretical understanding of AI in B2B marketing and provide practical insights for companies considering hybrid human-AI strategies. The study highlights the growing role of AI as a reliability, competent and personalized advisor in retail decision-making and paves the way for future research on ethical considerations and industry-specific applications of AI.engB2B RetailConsumer BehaviorArtificial IntelligenceRecommendation SystemsSatisfactionPurchase IntentionSDG 8 - Decent work and economic growthSDG 17 - Partnerships for the goalsmaster thesis204074061