Human-Centered AI Virtual Assistants: Enhancing Engagement, Trust, and Task Automation Through NLP and Emotional Cues

This study investigates how artificial intelligence (AI) virtual assistants enhance user engagement, trust, and task efficiency through natural language processing (NLP), voice recognition, and emotional cues. Using the Mind Perception Theory and Parasocial Relationship Theory as theoretical frameworks, this qualitative research interviewed twenty-two industry professionals experienced in AI assistants to explore user perceptions of human-like responsiveness in AI systems. Findings reveal that emotionally intelligent assistants improve task satisfaction and foster user trust, but also introduce ethical concerns around data privacy and emotional manipulation. The results offer practical guidelines for designing empathetic, secure, and user-centered AI solutions for enterprise applications to inform current and future AI-powered virtual assistants.