The rapid advancement of Generative Artificial Intelligence (GenAI) has transformed business communication, particularly in customer interactions. This dissertation investigates the implications of GenAI in marketing, focusing on its strengths, limitations, and the necessity for human oversight. The research comprises three interrelated studies: (1) a conceptual analysis introducing the CARE framework (Collaboration, Accountability, Responsiveness, Empowerment) to mitigate GenAI risks in business, (2) an empirical analysis assessing ChatGPT’s effectiveness in responding to customer complaints, identifying scenarios where GenAI underperforms due to issues like lack of concreteness, and (3) a linguistic comparison of managerial responses generated by human managers and two leading GenAI models—ChatGPT and Gemini—highlighting key linguistic factors influencing response effectiveness. Findings suggest that while GenAI-generated responses exhibit advantages in consistency, sentiment positivity, and efficiency, they lack specificity and human adaptability in handling procedural complaints. The results contribute to marketing and eWOM literature by providing empirical evidence on GenAI’s role in business communication, emphasizing the importance of human-AI collaboration for optimal effectiveness. The research offers theoretical insights into AI-human interaction and practical recommendations for businesses integrating GenAI into customer engagement strategies.