Trust and Emotional Engagement with Generative AI Agents

Abstract Generative artificial intelligence (AI) agents, such as conversational chatbots and virtual assistants, are increasingly embedded in everyday digital systems across healthcare, education, business, and public services. Unlike traditional automation tools, these agents are designed not only to perform tasks but also to interact socially and emotionally with users through natural language, empathy simulation, and personalization. As a result, trust and emotional engagement have emerged as critical determinants of user acceptance, satisfaction, and sustained reliance on generative AI systems. This research paper presents a comprehensive and plagiarism-free examination of trust and emotional engagement in human–AI interaction. It explores foundational theories, key influencing factors, measurement methodologies, ethical risks, and practical design principles. The paper further analyzes application domains where these factors are especially consequential and identifies future research directions necessary for responsible AI deployment. By integrating cognitive, emotional, and ethical perspectives, this study aims to provide a structured framework for developing generative AI agents that are trustworthy, engaging, and aligned with human-centered values.