This empirical study investigates the influence of AI-driven interactions on shaping consumer purchase intentions, focusing on the transition from online engagement to offline purchasing behaviors. As artificial intelligence becomes increasingly integrated into marketing strategies, its impact on consumer decisions remains a critical area of research. This study utilizes a mixed-method approach, combining quantitative data analysis from online consumer interactions with qualitative interviews from 300 participants who have experienced AI-driven customer service tools such as chatbots, personalized recommendations, and virtual assistants. The primary aim is to evaluate how these AI features affect consumers' willingness to make a purchase in a physical store after an online interaction. Results from logistic regression analysis suggest that personalized AI interactions significantly enhance the likelihood of offline purchases, with a 40% increase in consumer transition rates from online browsing to in-store buying. The qualitative data further reveal that effective AI interactions contribute to a heightened sense of trust and satisfaction, which are pivotal in influencing purchase intentions. However, the study also identifies challenges, including privacy concerns and the impersonal nature of some AI interactions, which could inhibit consumer conversion. This research not only sheds light on the pivotal role of AI in modern consumer behavior but also offers valuable insights for retailers looking to optimize their integrated online-to-offline marketing strategies. The findings are particularly relevant for enhancing customer engagement and tailoring AI tools to meet evolving consumer expectations in the digital age.