Behavioral health was once seen as secondary: invisible, underfunded and misunderstood. no longer. Its stigma fades away, and the economic cost of ignoring it is too steep to ignore. Employers, payers and policy makers are paying attention. But for patients and providers, the landscape is becoming increasingly difficult to navigate.
The shift in government policy is creating uncertainty, and the long-term effects of the pandemic are being understated. People worry about companies quietly throwing away EAPs, raising questions about what happens when the workplace stops prioritizing mental health. Meanwhile, we see a forked world emerge: Some people can really care while others turn to AI like chatgpt to manage issues like depression or obsessive-compulsive disorder. We are in the estimation and focusing alone cannot solve the problem.
With the surge in demand for behavioral health care, traditional models of care lag behind. A nationwide shortage of providers and growing clinician burnout has left millions of Americans living in communities without access to mental health professionals. For example, one in three adults struggle with anxiety and cannot get the care they need. Clinicians also see patients who need longer treatment and show more severe symptoms than in the past, forcing them to work with their ability to limit their work.
Behavioral health is reaching a breakthrough point as more people need care and fewer clinicians to deliver it. Virtual care and digital tools are no longer just hopeful, they are essential. This shift is helping to fuel today’s mental health AI boom. The market is expected to grow from nearly $88 billion in 2024 to $132 billion in 2032, up 50% in just eight years.
Thankfully, many emerging technologies have shown hope in alleviating stress. AI-driven tools are simplifying operations with automated workflows, smarter resource allocation and faster documentation. On the frontlines of care, digital applications and telehealth platforms are changing how people and access support.
However, not every new solution delivers on its promise. For providers, patients, payers, and employers, flooding of AI-driven screening tools, chatbots, and clinical decision-making systems makes the situation even more difficult (not easy) and cannot tell which tools really improve care and which tools just add noise.
In a market full of potential but vulnerable to over-invasion, it is fair to ask: Do we overestimate AI’s preparation for behavioral health?
Not all AI is created equally
The world of behavioral health is in trouble in AI, but its applications vary widely in complexity and impact.
Some tools are already making real impact. AI-driven intake assessment and symptom checkers help patients match patients to the appropriate level of care faster and more accurately. Automatic scribes and speech analysis tools reduce clinical documentation time and give providers more freedom to focus on the patients in front of them. Chatbots and mobile apps provide support between meetings to help patients stay and connect when they need it most. These are not futuristic promises. They are using solutions that reduce administrative stress, improve care delivery and make behavioral health more accessible.
But in other cases, the clinical credibility of artificial intelligence is far less convincing. Unlike radiology or cardiology, many behavioral health tools are built on shaky ground in the presence of clear FDA pathways: small sample sizes, biased datasets or no real-world tests. These models may produce confident results, but clinically flawed results, misleading care, putting patients at risk and exposing providers to legal and ethical consequences.
Instead of simplifying care, these tools force regulators to step in, especially when AI begins to influence diagnostic or treatment decisions. This won’t unlock efficiency. It adds to the already overburdened system.
Some direct-to-consumer chatbots and self-service apps are also overly high and inadequate, claiming to provide “therapeutics” support while lacking the ability to deal with crisis situations, clinical nuances, or complex mental health needs. Meanwhile, tools like Chatgpt do not claim to comply with security or regulatory standards, but are still used for emotional support by millions, simply because they are free and easy to access.
Like any rapidly growing market, behavioral health AI will be both breakthrough and malfunctioning. But despite the increasing pain, we still need to continue to push the field forward. Using the right guardrails, AI can help us build better behavioral sanitation systems. However, we need to be responsible for how it is deployed and for what reasons otherwise we may have negative patient outcomes.
What is the AI of the person in charge like?
Whether you are part of a large health system or running independent practices, evaluating behavioral health AI is more optimistic than optimism. It requires healthy doubt. Providers, managers, technicians and revenue managers who make these decisions cannot blindly trust flashy demonstrations or huge commitments.
AI tools that will really move needles in terms of behavioral health aren’t just about optimizing billing. Instead, they are based on clinical validation, consider providers, and are designed to reduce workload. Unlike the income cycle tool, it plays an important but invisible role, clinical solutions directly affect the patient experience and the clinician’s ability to provide care. They fight their technology stack by helping clinicians spend less time fighting their technology stack, and more time focusing on defining behavioral health relationships:
- Clinically, not only smart – Red flags include weak privacy protection, tiny training data sets or lack of peer review validation. Green Flag includes human models, clearly defined limitations, and focuses on enhancing rather than replacing clinical judgment. For example, AI robotics therapists must have a clear path to escalation, and at critical moments, clinicians circulate among clinicians, which can improve treatment and reduce adoption risks for patients and providers.
- Designed by providers, not just for them – The best behavioral health AI tools are built in collaboration with clinicians. Looking for Solutions developed from the start using actual provider inputs, not just usability feedback at the end. This collaboration leads to smarter design choices, smoother interoperability, and better adoption between care teams.
- Start small, prove value, and then expand – AI tools that should not be from pilot to system overnight. Find early wins: Better screening accuracy, less time on the document, and improve treatment adherence. These are signs of tools that are actually effective and worth expanding.
Artificial intelligence has made a difference in behavioral health. It is helping providers stay present with patients, ensuring evidence-based protocols are followed, and marking risks before a crisis.
But progress is unbalanced. Not every tool can be used. Not every system works well with the others. Not every platform understands the nuances of behavioral care. That’s not a failure. This is the reality of building new things.
To move forward, we need to share standards, smarter safeguards, and be willing to learn from effective methods and ineffective content. Behavioral health does not require technology to replace people. It requires respect for their technology, expanding what clinicians do best, and helping more people get the care they deserve.
This moment is not a chasing and hype. It’s about building a stronger foundation for future care. Together, we can do this correctly.
Photos: metorworks, Getty Images
Melissa Tran is CEO of Prosperityehr, who leads the company’s mission to modernize behavioral health infrastructure. Melissa is an experienced health technology leader with senior positions at EPIC, Bluetree Network, Tegria and Wisconsin University, and has deep expertise in clinical systems, virtual care and healthcare operations.
Dr. Heidi V. Carlson is a licensed psychologist and marriage and family therapist at the River Valley Center for Behavioral Health and Wellness, specializing in counseling psychology. She holds a PhD and a Master of Community Counseling from St. Thomas University, focusing on marriage and family therapy. Dr. Carlson has extensive experience in providing psychological and cognitive assessments and psychotherapy for individuals, couples, families and across hospitals, schools, inpatient and outpatient settings. Her specialization includes the development of trauma, brain development, attachment, adoption, mood disorders, and treatment programs. In addition to clinical work, she also provides a range of consultation and training on mental health topics for schools, hospitals and organizations.
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