As mental health needs grow around the world, AI is emerging as a critical tool to bridge gaps in care. From Africa to Latin America, AI-powered platforms and chatbots are being developed to expand access, support early detection, and complement human professionals. Experts caution that while the potential is enormous, ensuring safety, cultural relevance, and oversight is essential.
In Uganda, for example, helpline calls to Butabika Hospital are helping train an AI system capable of understanding local languages such as Swahili and Luganda, reports The Guardian. Researchers at Makerere University’s AI Lab and partner hospitals in Tanzania are analyzing anonymized call recordings to detect signs of depression, suicidal thoughts, and other mental health concerns. Joyce Nakatumba-Nabende, Head, AI Lab, explains that callers are “helping to create a therapy algorithm that works in local languages,” addressing a region where one in 10 people struggles with mental health challenges, but trained professionals are scarce.
“AI chatbots can deliver services faster and on a larger scale, reaching people who might otherwise avoid clinics due to stigma,” says Nakatumba-Nabende. The technology could even operate via SMS for those without smartphones or internet access, ensuring broader accessibility.
Latin America is seeing rapid AI adoption in mental healthcare as well. Platforms like Yana, an AI-powered cognitive behavioral therapy app, have reached 16 million downloads and now serve mostly adult users. Andrea Campos, CEO and Founder, Yana, explains that AI allows for “more natural, responsive, and personalized conversations,” helping users recognize and challenge negative thought patterns. Hybrid models that combine AI support with human therapy sessions can accelerate treatment, improve engagement, and expand accessibility without replacing professionals.
Similarly, Mindsurf uses AI to conduct validated emotional risk assessments and connect high-risk users with licensed therapists. “AI enables scalable, data-driven mental health solutions while maintaining clinical standards,” says Grecia Ávalos, Co-Founder and CEO, Mindsurf. By facilitating early detection and continuous monitoring, these platforms help address workforce shortages that otherwise limit timely care.
AI is also making its way into medical education. Medu, for example, integrates AI into training for healthcare professionals and students, offering real-time answers based on peer-reviewed medical content, supplementary videos, and interactive guidance. Medu’s AI, still in beta, is designed as a complement to traditional learning and may eventually simulate virtual patient interactions for clinical training.
However AI is not without risks. Misleading or overly simplified outputs — sometimes called “AI pandering” — can reinforce misconceptions if safeguards are not in place. Erick Ponce, President, The International Cannabis and Cannabinoids Institute, warns that AI may provide seemingly confident but inaccurate advice in sensitive areas. Ensuring ethical use, regulatory compliance, and oversight remains critical.
The Mexican Social Security Institute (IMSS) recently established a commission on AI governance and ethics to guide the use of AI in healthcare, emphasizing safety, data protection, and oversight. Héctor Valle, Executive President, FunSalud, notes that AI can assist physicians with recordkeeping, diagnostics, and decision-making but cannot replace human expertise.
Globally, AI in mental health represents both opportunity and responsibility. By combining culturally adapted algorithms, purpose-built platforms, and hybrid care models, AI can reach underserved populations while maintaining quality and safety. Campos emphasizes that AI should be viewed as an ally: “It is not here to replace human expertise but to augment and enhance our abilities, making support more accessible, efficient, and scalable.”
From helpline calls in Kampala to chatbots in Mexico and Brazil, AI is reshaping how mental healthcare is delivered, taught, and monitored. Its success, however, will depend on ethical deployment, ongoing oversight, and the integration of human judgment at every stage.