Mental health disorders impact nearly a billion people worldwide, yet access to traditional therapy remains limited due to high costs, therapist shortages, and stigma. AI-driven therapy solutions offer scalability, affordability, and continuous support, but lack emotional intelligence, social awareness, and ethical discernment. Meanwhile, human therapists provide deep interpersonal connection and adaptive treatment but face constraints like availability and burnout. This study explores the possibility of a hybrid therapy model that integrates AI-driven tools with human therapists to enhance accessibility and treatment outcomes while mitigating risks. Through a multi-phase empirical approach, we propose to examine patient and therapist perspectives, assess AI’s potential to augment therapy, and evaluate long-term engagement and effectiveness. Findings will contribute to the development of an ethical, structured framework for AI-human collaboration in mental healthcare, offering insights for clinicians, policymakers, and AI developers. This research aims to make mental health support more inclusive, efficient, and effective.