AI Use in Telebehavioral Health: Avoiding the Pitfalls
Every May we observe Mental Health Awareness Month. At the Upper Midwest Telehealth Resource Center, Mental Health Awareness Month provides us with the opportunity to highlight the importance of mental health services and foster discussions about how telehealth and digital health technology can reduce barriers to care.
Telehealth has become an important tool for behavioral healthcare by increasing access to counseling, psychiatric services, and support programs, especially for rural and underserved communities. Virtual care can reduce transportation challenges, shorten wait times, and allow patients to receive care from the privacy of their homes.
It seems to go without saying that telebehavioral health will continue to be a vital part of the telehealth landscape in the future. But with the widespread introduction of Artificial Intelligence (AI), what this involvement looks like is suddenly changing.
AI Prevalence
Artificial intelligence (AI) use is becoming increasingly common in telebehavioral health. Healthcare organizations are using AI-powered tools for appointment scheduling, clinical documentation, symptom monitoring, chatbots, and patient communication. AI seems to be at its most useful in healthcare when it serves to free up provider time from administrative tasks so they can spend more time with patients. Used this way, there are fewer ethical questions about how AI use is impacting patients.
But behavioral health is different. Workforce shortages and an increased need for mental health support, particularly in our rural communities, have led many to turn to AI as a potential solution. Behavioral health platforms exists that use AI to help identify signs of anxiety, depression, or emotional distress through patient responses or speech patterns.
Proponents argue that AI tools may help improve efficiency and expand access to care during ongoing behavioral health workforce shortages. Even outside of traditional providers, there are those who independently use AI chatbots for emotional support and mental health information. So, is AI the key to solving the country’s mental health crisis?
The reality, it turns out, is complicated.
Examining the Drawbacks
The first and most important fact is that AI systems necessarily lack genuine human understanding, empathy, and clinical judgment. Mental health care relies heavily on trust, emotional nuance, therapeutic relationships, and individualized clinical interpretation — areas where AI tools fall far short. At best, AI tools are ineffective for mental health treatment. At worst, they can be dangerous.
Experts have documented cases where AI chatbots provided misleading mental health information, reinforced delusional thinking, failed to appropriately respond to crisis situations, or even encouraged harmful behaviors. These risks are particularly concerning for vulnerable populations, including adolescents, individuals experiencing severe mental illness, or people in crisis situations. Healthcare professionals and researchers have also raised concerns about emotional dependence on AI tools and the possibility that patients may substitute chatbot interactions for professional care.
Privacy and data security are also major concerns because behavioral health information is highly sensitive. In addition, AI systems may reflect bias if they are trained on incomplete or non-diverse data, potentially leading to unequal outcomes for patients. Experts continue to emphasize that AI should support healthcare professionals rather than replace licensed mental health providers.
Responsible Use and Next Steps
So, what do we do about it?
AI adoption continues to grow across all sectors, healthcare included. Regardless, AI should be used to support — not replace — licensed clinicians. Human oversight remains essential, especially in situations involving diagnosis, crisis intervention, suicide risk assessment, and treatment planning.
Healthcare organizations can promote responsible AI use by developing clear governance policies, ensuring transparency about how AI tools are used, and evaluating technologies for safety, accuracy, and bias before implementation. Clinicians and healthcare leaders should also prioritize patient education so individuals understand the limitations of AI systems and know when to seek professional care. Regulatory oversight and evidence-based standards will likely continue evolving as policymakers and healthcare organizations work to establish safer frameworks for AI in mental health care.
Looking ahead, AI may continue to improve administrative efficiency, remote monitoring, and early identification of mental health concerns. However, the most effective approach will likely combine AI-supported tools with human-centered behavioral healthcare.
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