This paper investigates the integration of emotional intelligence (EI) into artificial intelligence (AI) systems, presenting key findings from a mixed-methods study including a large-scale survey. Major contributions include: (1) a comprehensive literature synthesis of affective computing advances and real-world applications; (2) a robust survey instrument measuring demographics, AI familiarity, emotional AI awareness, application preferences, trust factors, and ethical concerns; (3) empirical analysis combining quantitative results with qualitative insights; and (4) evidence-based recommendations for developers and regulators focused on privacy, bias mitigation, and cultural sensitivity. Findings reveal strong user interest in mental-health and educational applications, significant privacy and bias concerns, and demand for transparent, culturally adaptive emotional AI frameworks.