Artificial intelligence (AI) is being increasingly adopted in mental health care, with AI-powered chatbots such as Therabot, Woebot, and Tess providing therapeutic support and immediate, around-the-clock assistance. These tools are attracting users seeking alternatives to traditional therapy due to cost and accessibility, and are being used for issues including depression, anxiety, and eating disorders. A recent randomized controlled trial of the Therabot chatbot showed greater reductions in depression, anxiety, and eating disorder symptoms at both 4-week and 8-week follow-ups compared to a control group. Similarly, the Limbic chatbot, deployed in the UK, led to a 15% increase in mental health service referrals, with notable benefits for minority groups. AI is also being used to optimize administrative processes such as scheduling and referrals, and to support early detection and diagnosis through analysis of digital phenotyping and health records. Machine learning models can predict suicide risk and mental health crises with significant accuracy, enabling earlier interventions. Despite these advances, mental health professionals and regulatory bodies, including the Consejo Federal de Psicología, have raised concerns about the risks of relying on AI for therapy. Experts caution that AI lacks professional judgment and cannot replace human therapists, emphasizing the need for human oversight, data privacy, and ethical standards. The World Health Organization and other organizations have called for robust governance frameworks to ensure safe and equitable implementation of AI in mental health. Ethical considerations include potential biases in AI algorithms, transparency of decision-making, and the need for informed consent. There is also ongoing debate about the depth and quality of therapeutic relationships provided by AI chatbots, and the risk of exacerbating inequities if access to AI-driven services is uneven. Experts agree that these tools should complement, not replace, professional human care.