Policymakers And Lawmakers Eyeing The Use Of AI As A Requisite First-Line For Mental Health Gatekeeping And Therapy Intervention

In today’s column, I examine the controversial proposition that generative AI and large language models (LLMs) should be used as a requisite first line of mental health gatekeeping and perform initial mental health first aid by providing therapy intervention. This entails significant policy and legal implications and ramifications.

Let’s talk about it.

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 (see the link here).

AI And Mental Health

As a quick background, I’ve been extensively covering and analyzing a myriad of facets regarding the advent of modern-era AI that produces mental health advice and performs AI-driven therapy. This rising use of AI has principally been spurred by the evolving advances and widespread adoption of generative AI. For an extensive listing of my well-over one hundred analyses and postings, see the link here and the link here.

There is little doubt that this is a rapidly developing field and that there are tremendous upsides to be had, but at the same time, regrettably, hidden risks and outright gotchas come into these endeavors, too. I frequently speak up about these pressing matters, including in an appearance on an episode of CBS’s 60 Minutes, see the link here.

Background On AI For Mental Health

I’d like to set the stage on how generative AI and large language models (LLMs) are typically used in an ad hoc way for mental health guidance. Millions upon millions of people are using generative AI as their ongoing advisor on mental health considerations (note that ChatGPT alone has over 900 million weekly active users, a notable proportion of which dip into mental health aspects, see my analysis at the link here). The top-ranked use of contemporary generative AI and LLMs is to consult with the AI on mental health facets; see my coverage at the link here.

This popular usage makes abundant sense. You can access most of the major generative AI systems for nearly free or at a super low cost, doing so anywhere and at any time. Thus, if you have any mental health qualms that you want to chat about, all you need to do is log in to AI and proceed forthwith on a 24/7 basis.

There are significant worries that AI can readily go off the rails or otherwise dispense unsuitable or even egregiously inappropriate mental health advice. Banner headlines in August of this year accompanied the lawsuit filed against OpenAI for their lack of AI safeguards when it came to providing cognitive advisement.

Despite claims by AI makers that they are gradually instituting AI safeguards, there are still a lot of downside risks of the AI doing untoward acts, such as insidiously helping users in co-creating delusions that can lead to self-harm. For my follow-on analysis of details about the OpenAI lawsuit and how AI can foster delusional thinking in humans, see my analysis at the link here. As noted, I have been earnestly predicting that eventually all of the major AI makers will be taken to the woodshed for their paucity of robust AI safeguards.

Today’s generic LLMs, such as ChatGPT, Claude, Gemini, Grok, and others, are not at all akin to the robust capabilities of human therapists. Meanwhile, specialized LLMs are being built to presumably attain similar qualities, but they are still primarily in the development and testing stages. See my coverage at the link here.

The Current Situation Legally

Some states have already opted to enact new laws governing AI that provide mental health guidance. For my analysis of the AI mental health law in Illinois, see the link here, for the law in Utah, see the link here, and for the law in Nevada, see the link here. There will be court cases that test those new laws. It is too early to know whether the laws will stand as is and survive legal battles waged by AI makers.

Congress has repeatedly waded into establishing an overarching federal law that would encompass AI that dispenses mental health advice. So far, no dice. The efforts have ultimately faded from view. Thus, at this time, there isn’t a federal law devoted to these controversial AI matters per se. I have laid out an outline of what a comprehensive law on AI and mental health ought to contain, or at least should give due consideration to, see my analyses at the link here and the link here.

The situation currently is that only a handful of states have enacted new laws regarding AI and mental health, but most states have not yet done so. Many of those states are toying with doing so. Additionally, there are state laws being enacted that have to do with child safety when using AI, aspects of AI companionship, extreme sycophancy by AI, etc., all of which, though they aren’t necessarily deemed as mental health laws per se, certainly pertain to mental health. Meanwhile, Congress has also ventured into the sphere, which would be a much larger aim at AI for all kinds of uses, but nothing has gotten to a formative stage.

That’s the lay of the land right now.

Floating Proposition And Heated Debate

Suppose that a person wants to see a human therapist. Human therapists are essentially a scarce resource. They are relatively costly, they take a somewhat lengthy time to be produced (i.e., years of training, rigorous testing and licensing), there aren’t enough to go around (demand is far outstripping supply), and otherwise, there is a cogent argument that we should judiciously decide as a society whether seeing a human therapist is warranted in each individual case. There is a need to allocate the scarce resources where they properly belong. Don’t waste the resources.

How could this feasibly be done on a population scale?

The viewpoint is that since AI can readily work on a massive scale and handle millions upon millions of requests easily, we could have people make use of AI to first determine whether they can see a human therapist. It would be straightforward and quick to do. Merely log into some AI that has been established for this gatekeeper role. Voila, the AI would perform a screening process.

The range and depth of questions addressed by the AI would focus on a sort of pre-assessment. Does the person seem to have mental health conditions that merit access to a human therapist? Will the allocation of a human therapist to the person be suitably sensible, given the scarcity issue at play? Perhaps the person doesn’t genuinely need to see a human therapist, and therefore, there is no need to burden and waste human therapy time when it could be used for someone truly in need.

The proposition doesn’t stop there. The thinking is that since a person is undergoing the screening process via the AI, we might as well also have the AI perform an initial first-aid style mental health intervention. It could be that a person has a simple mental health aspect that the AI can help overcome. No need to route the person to a human therapist when the mental health status can be prudently handled by the AI.

Tap into the AI-driven therapy capacities.

Two Parts And The Claimed Benefits

All told, the proposition usually consists of a twofer:

• (1) AI as first-line mental health screener: AI acts as a gatekeeper to screen people before granting access to a human therapist.
• (2) AI as first-aid mental health therapist: AI serves as an AI-driven therapist to aid those who don’t yet seem to need a human therapist.

The benefits are that we reduce unnecessary consumption of human therapists, allowing the base of human therapists to concentrate on people who truly need such assistance. The screening or gatekeeping can be done at a huge scale while keeping the cost of screening extremely low. Screening is highly available. The AI could be accessed 24/7 and used anywhere a person might be.

The societal costs of psychotherapy would presumably be significantly reduced. No waste of resources or at least minimal waste in comparison to contemporary approaches to accessing human therapists.

People might be more open to seeking mental health therapy since AI is less intimidating and logistically easier to use. The current path involves having to seek out a human therapist, requiring difficult decisions about who to contact, and consuming therapist time to conduct similar pre-screens (for my discussion about the use of AI as a mental health referral mechanism, see my scrutiny at the link here). It could be that people holding back from seeking therapy would feel less inhibited to merely access AI and gauge what their status is, and then be seamlessly routed to a human therapist if needed.

Another byproduct would be that a form of standardization could be scientifically established and become a validated screening instrument that would be used by all, as encapsulated in the AI. The existing approach tends to involve screening of prospective clients and patients on a proprietary or idiosyncratic basis. Pretty much a one-sies and two-sies form of screening.

The bottom line is that AI becomes a mental health front door. AI would serve as a pragmatic public-health capability to the advantage of societal mental health.

The Downsides Are Aired

Whoa, comes an erstwhile retort, the alleged benefits need to be seriously weighed against the potential downsides.

First, as noted, two facets are being considered in the same breath. Maybe it’s more than we can chew. One viewpoint is that we should do only one, such as just perform the screening, but not do the second, the intervention. A less vocalized thought is that if we are only going to do one, do the second portion of the intervention, but don’t do the screening. It doesn’t necessarily have to be a twofer. We can separate the argument into two discernable distinct parts and use only one of the aspects.

That being said, the screening portion is often seen as less controversial than the mental health intervention portion. To clarify, both portions are highly controversial. I’m just noting that there tends to be more that can see the value of the screening, but that once the AI ventures into proactively offering mental health guidance, well, that’s a bridge too far.

Second, a question arises about how solidified the screening portion is. If it is a non-negotiable and a final decision made by AI, that raises ethical and societal heartburn. The screening could maybe be reasonably undertaken as long as the person being screened can either appeal the screening result or they can go around the screening. In other words, make the screening a voluntary option. Don’t trap everyone into being kept from a human therapist because of what AI has determined. There might be incentives for those who use the AI, and maybe disincentives if you don’t (maybe), though in the end, the AI should not be the exclusive gatekeeper.

Third, the AI is bound to render false positives and false negatives. People who ought to see a human therapist might get screened out. What then? Not good. And people who don’t need a human therapist might get screened in. This is potentially a waste of a scarce resource. Sure, a referral to a human therapist will undoubtedly make that determination too, but meanwhile, the act of having the human therapist do a second round of screening is a consumption of that resource.

Fourth, when AI does the screening, who will be held responsible for screening out someone who turns out to have had a true need for a human therapist and was essentially denied via the AI? Is it the AI maker? Is it an insurer that is relying on the AI? A concern is that no one will be held responsible or that finger-pointing will obfuscate responsibility.

Fifth, a slippery slope might arise when it comes to the intervention portion. Here’s how that goes. Initially, the AI is supposed to do just first aid when it comes to mental health intervention. Gradually, this becomes a new norm. Inch by inch, we ratchet up the AI-driven mental health guidance and reduce the flow to human therapists. A worry is that this will lead to the normalization of a minimal and perhaps questionable level of mental healthcare.

Recent Points Raised

A recent article in JAMA Psychiatry brought up the topic of AI as a transformative element of mental health and included a brief look at the gatekeeper and first-line intervention discourse, doing so in the piece entitled “Artificial Intelligence and the Potential Transformation of Mental Health” by Dr. Roy H. Perlis, JAMA Psychiatry, January 14, 2026, and made these salient points (excerpts):

• “Some of the risks associated with AI are not inherent in the technology itself, but reflect the way in which it may be deployed to alter care delivery in ways that are harmful for patients. For example, chatbots could become a required first-line outpatient treatment for many psychiatric disorders, a new tier in the treatment approval process.”
• “It is easy to imagine an insurer requiring evidence that a patient has tried to complete a full course of app-based CBT before authorizing any further treatment.”
• “Telehealth companies have already demonstrated an enthusiasm for diverting patients to such lower-cost interventions. In one such controversial decision, a telehealth clinician unilaterally elected to triage all depressed individuals with moderate symptom severity away from individual psychotherapy.”
• “Done thoughtfully and carefully, automated first-line therapy is likely to benefit some individuals. However, as a mandated first step, chatbot-based therapy could delay effective treatment for many patients who could benefit from it.”
• “Even if an AI technology is cost-effective, a society may decide that the particular cost-cutting strategy it embodies should not be applied. For example, if chatbots are not to be mandated first-line treatment by some insurers, this may need to be accomplished with legislation.”

This handily brings up the policymaker and lawmaker considerations, which might be depicted as these two divergent possibilities:

• (1) In favor of: Enact laws that support the twofer approach.
• (2) Opposed to: Enacts laws that ban or prohibit the twofer approach.

Let’s take a further step into each of those avenues. I will provide the kind of language that might be used to draft such laws.

Drafting A Law In Support Of The Approach

Regulators who are aiming to craft a state law that would be in support of the approach might make these key points underlying the basis of the proposed law (illustrated as example draft language).

• State Mental Health Access and Early Intervention Act
• 1. Mental health conditions impose substantial personal, social, and economic costs on residents of the State.
• 2. Access to licensed mental health professionals is limited by workforce shortages, geographic disparities, and cost barriers.
• 3. Advances in artificial intelligence systems enable scalable, standardized mental health screening and early supportive interventions.
• 4. Early identification and intervention may reduce the severity, duration, and cost of mental health conditions.

Therefore, this law is to be established as follows:

• Purpose. The purpose of this Act is to expand access to mental health support by requiring the use of state-approved artificial intelligence systems as an initial screening and early-intervention mechanism, while preserving access to human clinicians when clinically indicated.

Various provisions in the law would define the meaning of the terms used in the bill, outline the scope of the law, stipulate limitations and exceptions, and address other crucial facets.

An especially vital portion would encompass matters of oversight, certification, and auditing, such as these example specifications:

• Certification. The State Department of Health shall certify Artificial Intelligence Mental Health Systems for use under this Act. Certification shall require: (a) demonstrated validity and reliability, (b) bias and equity impact assessments, (c) data security and privacy safeguards, and (d) regular third-party audits. Certification may be suspended or revoked for noncompliance or demonstrated harm to the public.

Drafting A Law To Prohibit The Approach

Regulators who are aiming instead to craft a state law that would explicitly ban or prohibit the approach might make these key points underlying the basis of their proposed law (illustrated as example draft language).

• State Mental Health Safety And Protection Act
• 1. Mental health assessment and intervention require clinical judgment, contextual understanding, and ethical responsibility that cannot be fully replicated by automated systems.
• 2. The use of artificial intelligence to screen or intervene in mental health care poses risks of misclassification, harm, discrimination, and erosion of patient autonomy.
• 3. Limiting access to licensed mental health professionals via the use of artificial intelligence undermines informed consent and may delay necessary care.
• 4. The State has a compelling interest in ensuring that mental health services remain grounded in human professional responsibility and accountability.

Therefore, this law is to be established as follows:

• Purpose: The purpose of this Act is to prohibit the use of artificial intelligence systems as mandatory gatekeepers or providers of mental health screening or intervention, and to preserve direct access to licensed mental health professionals.

Among the various stipulations would be a passage that carefully specifies the nature of the prohibition. An example would be this type of language:

• Prohibition. A Covered Entity shall not require an individual to interact with an Artificial Intelligence System for the purpose of mental health screening or mental health intervention as a condition of: (a) access to a licensed mental health professional, (b) authorization of mental health services, or (c) determination of medical necessity or coverage. Any requirement, policy, or practice that conditions access to mental health services on AI use is considered legally void and unenforceable.

This wording would need to be nailed tight, else some entities might try to claim a loophole exists and proceed as though the prohibition did not apply in their circumstance.

The World We Are In

Let’s end with a big picture viewpoint.

It is incontrovertible that we are now amid a grandiose worldwide experiment when it comes to societal mental health. The experiment is that AI is being made available nationally and globally, which is either overtly or insidiously acting to provide mental health guidance of one kind or another. Doing so either at no cost or at a minimal cost. It is available anywhere and at any time, 24/7. We are all the guinea pigs in this wanton experiment.

We need to decide whether we need new laws or can employ existing laws, or both, and stem the potential tide of adversely impacting society-wide mental health. The reason this is especially tough to consider is that AI has a dual-use effect. Just as AI can be detrimental to mental health, it can also be a huge bolstering force for mental health. A delicate tradeoff must be mindfully managed. Prevent or mitigate the downsides, and meanwhile make the upsides as widely and readily available as possible.

A final thought for now.

Benjamin Franklin famously made this remark about law: “Laws too gentle are seldom obeyed; too severe, seldom executed.” The question facing society is what, if any AI laws should be established, and to what degree can they be suitably balanced and just. I wager that even Benjamin Franklin would find that a great challenge.