Mental health disorders have been affecting approximately 970 million people worldwide, with depression and anxiety being the most common conditions. The global mental health issues continue to rise, compounded by limited access to qualified professionals, insufficient funding, and increasing demand, particularly among younger populations who favor digital forms of therapy. Artificial Intelligence (AI) offers promising solutions by supporting symptom screening, triage, conversational assistance, risk prediction, and integration into digital care platforms. However, many AI tools lack sufficient clinical validation and transparency regarding their value, raising concerns about trust, ethical use, and alignment with patient and clinical priorities. This study addresses these challenges by exploring the intersection of AI and value creation in mental healthcare. Employing qualitative analysis based on a literature review and semi-structured expert interviews, the research examines how professionals perceive and articulate the process of value creation through AI technologies. It investigates the types of value generated for both patients and providers and identifies ongoing challenges related to commercialization pressure, clinical relevance, and integration within mental healthcare systems. The findings provide insights into the complex dynamics of AI adoption in mental health, emphasizing the need for evidence-based development and stakeholder alignment to realize meaningful value. This study contributes to academic and practical understanding of AI’s role in enhancing mental healthcare delivery while highlighting critical areas for future research and policy development.