<p>Artificial intelligence and conversational chatbots are increasingly integrated into organisational communication systems. Despite their technical sophistication, user acceptance often hinges on emotional and social factors such as trust and authenticity rather than system performance. Understanding these dynamics is essential for achieving genuine digital maturity. This short communication introduces a conceptual framework for chatbot acceptance that unites technical, emotional, and ethical dimensions. The goal is to extend existing acceptance models by highlighting empathy and perceived authenticity as core determinants of user engagement. The paper employs a conceptual synthesis of established acceptance models (TAM, UTAUT) with insights from psychology, communication theory, and design ethics. This interdisciplinary approach serves to redefine acceptance as an adaptive and emotionally informed process. Findings indicate that users value conversational authenticity and empathy over precision or speed. Transparent and context-aware chatbot design increases trust and sustained use, whereas cold or intrusive interactions reduce acceptance. Emotional resonance and ethical integrity emerge as pivotal success factors. Acceptance in conversational AI depends on aligning machine logic with human emotion. Designing chatbots that are not merely efficient but human-compatible can enhance trust and interaction quality. The proposed model encourages a shift from usability-driven design toward emotionally intelligent AI communication.</p>