Not enough therapists for the rising demand of mental health therapy. One solution uses non-specialist labor for task-sharing. AI can help too. Here's the inside scoop.
In today’s column, I examine a rising interest in parsing out the activities of performing mental health therapy , of which AI could be a handy tool in assisting the enactment of labor-based task-sharing arrangements.
Note that the AI usage in this approach isn’t actively enlisted to perform therapy and instead is simply used for subtle guidance when enlisting new labor to aid therapy.Here’s the deal. The available supply of mental health professionals is woefully insufficient to meet the growing needs for mental health therapy services. One possible solution is to bring non-specialists into the fold and allocate some of the therapeutic tasks to them, doing so cautiously and sparingly. This involves a potentially significant logistical and management-focused effort, and thus, the use of AI could be advantageous to streamline the arduous task-sharing endeavor .This analysis of AI breakthroughs is part of my ongoing Forbes column coverage on the latest in AI, including identifying and explaining various impactful AI complexities . Given the assumption that the overall tactics and strategies are understood, what can be done to aid the task-sharing pursuit?For the mainstay activities involved in task-sharing of mental health services, I will walk you through how it is that AI can be beneficial. The AI doesn’t have to be used in every nook and cranny. That being said, we dare not overlook tasks and subtasks that could be constructively boosted due to sensibly incorporating AI. Observe that I mentioned that the AI needs to be sensibly incorporated. If you merely toss AI in this realm in a scattergun fashion, do not expect good results. AI could end up being a distractor. The AI could even be negative, causing troubles and introducing errors that otherwise might not have arisen. AI is never a silver bullet that solves all problems. The use of AI must be done judiciously. Watch for issues. Plan properly. Keep on top of what the AI is doing. And so on.Fortunately, a newly released field guide provides handy insights for incorporating AI into the task-sharing of mental health therapy. The guide is entitled “Mental Health And AI Field Guide” and was devised by Grand Challenges Canada, McKinsey Health Institute, and Google, posted online July 7, 2025, and included these selected key points : “Access to mental healthcare is limited worldwide, partly because there is a shortage of trained mental health professionals, especially in low-resource settings.” “This field guide introduces a model by which AI could help mental health task-sharing programs scale by supporting specialists and nonspecialists performing their respective roles.” “Task sharing is an evidence-based solution that increases access to care. In this approach, specialist healthcare professionals delegate specific tasks to trained nonspecialist providers to deliver direct mental health services to the public.” “It is important to acknowledge that the application of AI in task-sharing models is new and only a few pilots have been conducted.” “Many of the ideas outlined in this field guide are theoretical and have not yet been widely tested in real-world settings.” You can perhaps see from those excerpted points that the new guide is full of useful insights. It provides important indications and offers real-world examples. The aim is to get the topic of task-sharing on the table and illuminate the role of AI in that exciting and emerging endeavor. For those of you who are researchers in psychology, psychiatry, cognitive sciences, artificial intelligence, etc., you might contemplate performing research that would empirically examine the use of AI in this task-sharing model. We need to have rigorous studies that shine the light on what works and what doesn’t. There is ample opportunity to conduct fresh and original research in AI for mental health by tackling aspects of this particular topic.According to the field guide that I noted above, the authors have opted to present a task-sharing model that consists of six major phases:The life cycle starts when you first conceive of doing task-sharing. In the first phase, you would take an outlined standardized set of tasks and adapt those to the situation at hand. Each situation will differ. If you are in a low-resource circumstance, that will dictate what options you have available. In a high-resource setting, you undoubtedly have more choices of what to do. After completing the first phase, you move to the second phase and identify the non-specialist candidates for serving in the task-sharing arrangement. They become your trainees. The third phase entails training them in whatever tasks have been parceled out. The fourth phase has you assigning the trained non-specialists to their respective tasks. The fifth phase involves monitoring their performance and undertaking interventions as required. The last phase is the completion of the program. This involves tying up any final aspects. You would hopefully do a lessons-learned and be prepared to start up another similar program at a later date.Reviewing Candidates: “AI tools can be used to review candidates’ resumes, assessing skills suited for delivering mental health interventions after having collected basic information.”“AI algorithms can consider provider experience, language, and client complexity and needs to match the client with the right care provider and reduce wait times — ultimately improving adherence and coverage.”“Algorithms could augment detection of red-flag symptoms or behaviors of clients during screening responses to indicate which clients are higher risk and provide these insights to the care provider.”“AI tools could provide on-the-spot recommendations for care providers and show them the next steps they can take, including potential responses they could provide to clients based on intervention protocols.”“AI can scan session transcripts for meaningful phrases or steps to confirm adherence to intervention protocols, with the results of the scan available to be accessed after every session.”AI As Therapist The 800-pound gorilla in the mental health arena consists of asking the unabashed question of what degree AI should play a role in conducting therapy. I’ve emphasized that we are entering into an era that disrupts the classic duo of therapist-patient and is moving us into the new era of the triad, consisting of the therapist-AI-patient relationship and artificial superintelligence , it could be that the AGI/ASI is the primary therapist, while the human therapists and non-specialists are ancillary add-ons (see my discussion atTask-sharing is a thoughtful means of coping with the imbalance between the need for mental health therapy and the prevailing constrained pool of available mental health professionals. If done properly, it is possible to greatly magnify a set of therapists into a vast array of extended therapist-like addons. The catch is that it is all still labor-based. How much added labor can be mustered? How well will that added labor perform their assigned tasks? How much time shall be usurped from therapists to keep the added labor on target? Etc.All you need to do is add more computational power, and you can immensely scale until the cows come home. Of course, you must ensure that the thing you are scaling is going to be doing the right thing. Scaling something sour and dour will insidiously spread sourness and dourness to a wider audience.William Shakespeare famously said this: “We know what we are, but know not what we may be.” Mental health professionals cannot sit around and languish in the days of doing their prized efforts without modern-day AI. AI is here. AI is advancing. Rapidly. Mental health professionals might know what they are today, but that’s not sufficient. They need to be looking ahead to what they will be. The future, entailing advanced AI, shall become an integral part of their world. To be, or not to be.
Large Language Models LLM Chatgpt Openai GPT4-O O1 O3 Mental Health Therapy Psychology Psychiatry Cognition Advice Guidance Task-Sharing Arrangement Model
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