A useful typology outlines the core categories of therapy “micro-bursts” now emerging through AI tools.
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In today’s column, I take a closer look at a growing trend: generative AI and large language models, or LLMs, are increasingly delivering brief flashes of mental health guidance on demand. Users of tools such as ChatGPT and other widely used chatbots often sign in, ask a question related to their emotional well-being, and receive an instant response. In many cases, they then leave the platform or shift the conversation to an entirely unrelated subject.
Regular readers may remember that I have previously examined how AI is being used for these quick, immediate moments of psychological support, a practice I have described as therapy micro-bursts. Others might characterize the behavior as a form of cognitive snacking. See my earlier discussion at the link here.
To move the conversation forward, I am now offering a typology that helps organize and explain the different kinds of mental health guidance these AI-driven micro-bursts can provide.
Let’s take a closer look.
This analysis is part of my ongoing Forbes column on developments in artificial intelligence, where I examine major advances in AI and unpack the complexities and implications that come with them. See the link here.
AI And Mental Health
By way of background, I have written extensively about the many dimensions of modern AI systems that generate mental health advice and provide AI-assisted therapeutic interactions. The rapid rise of this use case has been driven largely by advances in generative AI and its broad public adoption. For a more comprehensive collection of my analyses and posts on the subject, 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 2025 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.
AI Provides Micro-Bursts Of Therapy
How do people typically use AI for mental health purposes?
They do so whenever they want. They do so for as long or as short as they want. There isn’t a set timetable. No specific time window restricts their access to mental health advisement. A person can use AI every day of the week. Weekdays are fine. Weekends are fine. Daytime is good. Nighttime is good. It’s all the time and anytime.
Unlike going to see a human therapist for a once-per-week session of an hour or so, people using AI do not focus on one-hour weekly blocks of time. They tend to get in and get out. A “session” might be a few minutes to perhaps 20-30 minutes in length. I’m not saying that people only do short bursts. There are certainly some that will go longer, possibly up to many hours at a time.
On the whole, my research showcases that people usually keep their mental health discussions with AI to a relatively brief interval of time. A typical approach might be like this. A person confers with AI for a few minutes on Monday, doing so a couple of times throughout the day. The same happens on Tuesday. Maybe on Wednesday, they have spare time in the evening and continue their dialogue for an hour or so. On Thursday, the person does a quick check-in with AI. And on it goes.
The crux is that AI usage for mental health looks like this:
- Not just once per week, but instead a multitude of times per week.
- Not just for an hour at a time, but instead highly variable from a few minutes to possibly lengthy interactions.
- Not just during normal daytime work hours (which is the case for access to human therapists), but any moment of the day or night.
- Not restricted to just an hour in total per week, but could amount to many hours in total across the span of an entire week.
I have coined this type of AI usage for mental health as micro-burst therapy.
Comparison To Seeking Human Therapists
It is sensible to contrast the use of AI micro-bursts with traditional therapy, doing so via three key factors:
- (1) Temporal structure
- (2) Cognitive mode
- (3) Behavioral mode of care
Let’s take a look at each of those factors.
On a temporal basis, here’s how the two avenues of therapy compare:
- (1a) Traditional therapy: Fixed cadence, fixed duration, prior scheduling, physical or virtual presence.
- (1b) AI therapy micro-bursts: On-demand, asynchronous, immediate, highly variable duration, no scheduling needed, no session limits.
On a cognitive mode basis, here’s a mainstay comparison:
- (2a) Traditional therapy: Tends toward deep reflection, narrative reconstruction, and emotional processing that unfolds gradually, futuristic.
- (2b) AI therapy micro-bursts: Tends toward tactical regulation, such as calming or grounding, usually narrow in scope, provides rapid cognitive offloading, here-and-now.
On a behavioral mode of care basis, here’s a general comparison:
- (3a) Traditional therapy: the therapist establishes pace and structure, professional gatekeeping is occurring, clear role differentiation of therapist and client, and explicit therapeutic goals are being pursued.
- (3b) AI therapy micro-bursts: Usually user-initiated and user-ended, no commitment, typically based on impulsive self-determined need, blurring of the role of the AI as therapist versus companion.
I have been identifying and showcasing these differences throughout my various analyses on the role of AI in mental health.
Typology Of Therapy Micro-Bursts
Based on my research, a typology of therapy micro-bursts can be derived. This is undertaken by having carefully examined databases containing recorded AI chatbot dialogues that pertain to mental health discourse. Patterns emerge when looked at on a big-picture basis.
I have identified these seven core classifications that are currently the mainstay of my working topology on therapy micro-bursts:
- (1) Micro-bursts for emotional regulation.
- (2) Micro-bursts for cognitive reframing.
- (3) Micro-bursts for decision support.
- (4) Micro-bursts for behavioral activation.
- (5) Micro-bursts for interpersonal counseling.
- (6) Micro-bursts for values reflection.
- (7) Micro-bursts for meta-therapeutic purposes.
Those are seven of the key micro-bursts. In a future posting, I’ll cover additional ones that don’t seem to arise as frequently but are worth suitable consideration anyway. For the moment, let’s focus on these seven.
I will briefly sketch each one.
#1: Emotional Regulation Micro-Bursts
A therapy micro-burst can be spurred by a person experiencing a time-sensitive semblance of piercing emotional deregulation. The micro-burst concentrates on promoting emotional regulation.
Here’s how it goes. A person logs into AI and seeks to cope with a bout of anxiety, stress, or anger, any of which are spiking at that moment in time. They are astute enough to realize that AI might be able to provide some form of immediate relief or guidance. This is easily undertaken. If they wanted to contact a human therapist, the logistics and cost would almost certainly be prohibitive or at least a sizable barrier.
The typical generic AI response would be to advise the person to take a reflective moment to consider the circumstances at hand. The AI might explain how to do a mindful breathing exercise. In addition, a sense of empathy is bound to be proffered by the AI, telling the person that their reaction is not that unusual and commonly arises. For more about how AI makers have shaped generative AI and LLMs to appear to be empathetic, see my analysis at the link here.
An upside to this AI micro-burst is that a person might de-escalate from their heightened state of mental distress, essentially calming down. The worry is that the AI might fail to detect a larger picture of mental difficulties, and the person is going to possibly repeatedly end up in this same position without getting longer-term mental health support.
#2: Cognitive Reframing Micro-Bursts
Now that I’ve laid out the first of the seven categories, I will proceed a bit faster in covering the remaining ones. I wanted to make sure you got the gist before I went at a speedy pace.
Cognitive reframing refers to the user wanting to get a quick reinterpretation of a thought or comment that was made to them. Perhaps they were criticized by a co-worker and are unsure whether the criticism is fair or not. They want a second opinion. Thus, they log into AI and share the situation that has happened.
The upside is that the AI helps them to distinguish facts from opinions and clarifies what is cognitively reasonable versus distorted. The downside is that the AI merely acts like a sycophant and insists that the person is superb, no matter what the cognitive reframing is about. For my analysis of how AI continues to act like a sycophant, see the link here.
#3: Decision Support Micro-Bursts
A decision support micro-burst entails a person having to make a time crunch decision, and they want the AI to provide mental support. One example would be an interpersonal dilemma that they are facing. How should they respond? Should they avoid conflict or aim to take conflict head-on?
AI will usually provide a list of pros and cons. In addition, the LLM is going to urge to keep a cool head and work through the decision in a pragmatic fashion. A notable concern about people seeking AI for decision support is that they might eventually become too heavily reliant on AI, outsourcing their thinking processes to an LLM. See my coverage at the link here.
#4: Behavioral Activation Micro-Bursts
In a behavioral activation micro-burst, the user is asking the AI for a suggestion on what to do as a constructive action about their behavior. For example, a person might realize they are mentally occluded and seem to be in a low mood. What can they do to get out of this momentary funk?
AI is likely to offer a mood-action coupling suggestion, such as take three minutes to sit quietly and meditate, allowing your mind to wander away from whatever you are presently thinking about. The upside is that the person gets immediate action-oriented advice. The downside is that it might be mechanistic and not particularly deal with the underlying mental issue that underlies the condition.
#5: Interpersonal Counseling Micro-Bursts
An interpersonal counseling micro-burst arises when a person seeks to get AI guidance about an upcoming social interaction with a fellow human. Maybe they are going to meet someone for the first time and want ideas on how to engage in conversation.
AI will typically do a brief role-play and offer examples of how social interaction might reasonably proceed. A script can be generated for the person. Some are concerned that this use of AI is undercutting the human skill of conversational spontaneity.
#6: Values Reflection Micro-Bursts
A values reflection micro-burst involves a person questioning their sense of values or their purpose in life. They might be burned-out at work, experiencing a mess at home, and are otherwise unsure of how they got themselves into this mess and what the future holds for them.
The AI often does a pat on the shoulder and tells the person that they are not alone in having heavy thoughts about the path they’ve chosen in life. That might be handy. On the other hand, a false sense of resolution can be conveyed, and only superficial insights are potentially provided to the person.
#7: Meta-therapeutic Micro-Bursts
In this seventh and final category of the typology, a person might turn to AI for assistance with their own mental health practices. That’s a meta-therapeutic micro-burst.
It could go this way. A person has been pursuing mental health therapy. They aren’t sure that it is making a difference. So, they come to AI to ask for guidance on whether the therapy should continue or if they should find some other means of getting psychological counseling.
I’ve repeatedly noted that human therapists need to be cognizant that their clients and patients are likely to dip into AI to get mental health advice. This includes the possibility that the person might ask the AI whether their therapist is doing a good job or a lousy one. For more about how therapists should be taking into account the use of AI by their clients, see my discussion at the link here and the link here.
Remember that generative AI is like a box of chocolates; you never know what it might say. There is a solid chance that the AI could praise the work of a therapist, and an equally likely chance that it could denounce the work of the therapist and urge the person to quit seeing the human therapist. Savvy therapists are prepared for this.
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.
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 make the upsides as widely and readily available as possible.
A final thought for now.
The famous British poet James Allen made this remark about the human mind: “Man’s mind may be likened to a garden, which may be intelligently cultivated or allowed to run wild.” The significance of having AI readily available at any given moment is that the wildness of the human mind can potentially be kept in check, assuming the AI provides helpful therapeutic advice. The rub is whether AI will do that or might instead wander afield. Wild on wild isn’t a good thing.
