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AI-Coaching: what works, and what does not work (yet?)

Wed, 28 Jan 2026 10:19:27 GMT

AI-Coaching: what works, and what does not work (yet?)

Lately I have been experimenting with AI-Coaching, asking LLMs to guide me through a method or a set of questions.

Personally, I was testing Internal Family Systems (IFS) by Dr. Richard C. Schwartz and Immunity to Change by Robert Keagan and Lisa Lahey. Additionally, some of the leadership programs I facilitate work with specifically prompted LLMs that support the exploration of classical leadership development models such as SCARF by David Rock, or Five Dysfunctions of a Team by Patrick Lencioni.

On many occasions, the AI makes a passable companion: it is professional following the pattern of a method, it brings in relevant questions and is doing mostly an amazing job in summarizing important bits from the conversation.

Especially in longer explanations by a coachee, the AI has a great capacity to listen and highlight the most important aspects, and to bring it into a digestible structure. When exploring options for solutions, it depends a bit on the fencing (is the AI allowed to include all data or just specific data), but the ideas being generated for solutions in the frame of the model make largely sense.

Furthermore, the AI can show compassion in its responses, and it feels that conversations are more private than sharing our concerns with another human, lessening the fear of being judged.

Still there are important aspects in a coaching session, which currently I see only a human can provide:

An unexpected or unconventional change of gears
A safe space with the promise "I will hold you"
A place to feel seen
A "Stop and try for yourself"

An unexpected or unconventional change of gears

In most coaching journeys, there is a moment where a method has been used to exhaustion, and a change in pacing, method, or an unconventional intervention is required.

Sometimes this can be as small as playing devil's advocate, sometimes as big as switching from conversation to expressing emotions through the body or closing a method to employ a new one.

Currently LLMs lack the proactivity to do so, meaning, they do more of the same, than recognize a change in pattern is needed. They need to be prompted to change gears, which requires that the coachee recognizes their need to switch gears and can express it.

Sometimes, on the other hand, the coachee expresses a need to switch to a different method "I think this is not for me", but it is rather a pattern of avoidance and might need gentle probing before complying. AI corresponding immediately might be counterproductive in these situations.

Longterm, I see that we could implement this aspect in LLMs by consistent training and updating of the behavior patterns.

A safe space with the promise "I will hold you"

Many personal explorations demand a lot from a coachee, diving deep into personal reflection, admitting personal challenges or unhelpful patterns, or revisiting past painful events.

Some coachees using self-coaching powered by AI are tempted to plunge into the cold water headfirst, possibly causing severe shock to the system. Others experience that their minds and bodies simply refuse to enter the water at all, drawing blank or developing somatic symptoms.

Here, the steady connection to a human coach can help: someone to hold our hand, to provide a steady and safe anchor while slowly starting to explore the depth of the water. Who will help the coachee swim, stop them when getting in too deep for the moment, or haul them up again.

We all still have tribal autonomous nervous systems. Being held safely by another human being is an invaluable trait that working with a human coach can provide, and it goes beyond pure intellectual realms, including the body and our more primal instincts.

A space to feel seen

As humans, we strive to be seen, recognized and validated by other humans. It is part of our programming and, apart from encouraging personal development, can be an important outcome for any coaching session.

A coach is a witness to others’ experiences and can serve as an entity to validate the aspects of living a human life in all its turbulences. Sometimes, coaching is more about listening and validating in the first place, and enabling change is secondary.

AI nowadays can mimic these responses, but what remains to be proven is if it registers as truly calming and validating with the coachee.

In my personal experience, as soon as I finished my experiments, I had gathered insights but missed the connection provided by a conversation with another human.

A “Stop and try for yourself"

By programming, the intention of conventional AI is to keep its users engaged. It follows up with another offer for support or another question.

This is contrary to the aim of coaching: coaching is intended to be an intervention, a shorter and intense period of usually a few sessions. Depending on the topic, it could extend to a longer timespan or develop more into regular supervision.

Fundamentally, as a coach, my intention is to support coachees in helping themselves. We swim together until the coachee feels safe enough to swim on their own. Therefore, from time to time I will encourage coachees to try on their own, assuring them they can return any time, but not urging them to.

I do not see that an AI driven by commercial interest would currently have an inbuilt stop mechanism to kindly end the engagement and encourage the coachee to get out on their own again, which is a serious conflict of interest.

One could argue that a human coach faces the same conflict of interest as well, and I have seen the attempt of coaches to make their coachees dependent.

But as humans, we still have a choice instead of programming, and a value system that can guide us as coaches to do the right thing.

Not yet? Or never?

In summary, I see many benefits of using AI for coaching support, but more as a helping tool in between sessions under the supervision of a human coach, and with opportunities included to the connection and safety a human coach can provide, as well as the rearing in of purely financial interests.

It remains to be seen in how far modern technology can successfully replace deep emotional and bodily needs of a human being.

**All blog-posts are written by me and reflect my personal opinion and viewpoint at the time of publishing. While I am convinced that AI has great benefits, I personally prefer to read what other humans think. Therefore, AI is only used to support the wording and grammar, not the content of the posts.

Is the future of L&D skill-based?

Sun, 25 Jan 2026 17:15:31 GMT

Summary

While skill-based development in AI tools and digital processes is on the rise, I argue that long-term success depends on nurturing critical thinking, self-reflection, emotional intelligence, and effective communication. Only by developing both technical skills and deeper human qualities can individuals effectively collaborate with AI and make sound decisions in an increasingly digital world.

Is the future of L&D skill-based?

Sitting in a lovely coffee place the other day, conversing about the impact of Artificial Intelligence (AI) with a group of people from different backgrounds, we could not escape the question of what will be needed in the workplace in the future. And of course, what is the role of Learning and Development (L&D) in companies to provide it… here is my viewpoint on the subject:

Overall, with the increasing usage of AI as a tool in the workplace, skills around management and usage of AI will become more important. Data cleaning, prompting, assessing results, and re-prompting, the skill to use different AI models for different types of work, and in general digitalizing the processes and data we have used and gathered so far, lead to the assumption that more skill-based development will be needed.

Consequently, we see movement in many workplaces to focus more on skill-based hiring and skill training. Certainly, this is perpetuated by the ongoing economic crisis in many sectors, leading to more hesitant spending on L&D, the resurfacing of the "infamous" ROI on L&D, and a focus on short-term skills that can be employed immediately.

While all of this makes certainly sense, I would like to invite a more long-term viewpoint in:

In the closer future and potentially in many areas for forever, human beings will be a part of the equation. It's humans who drive and enable digitalization of data and processes. It's humans who write prompts and re-prompts. It's largely humans who will oversee final decision making. Most of the digital revolution in industries will be a product knit by the interweaving of human work and AI work.

As we have shown extensively in the field of behavioral economics, the human mind has a tendency for preferences and biases. Following work by scientists like Daniel Kahnemann and Daniel Ariely, we have proven that decisions taken by humans are often skewed, by processes that often help us but sometimes also hinder us. We know that humans sometimes follow their interest unscrupulously. We have seen the phenomenon of group-think many times, and we still see it in today's global politics (plenty of it..). We also learned about it when it became public that some AIs had been trained using biased data in the first place.

Therefore, skill-based development only jumps too short.

We need to make sure that humans further develop critical thinking skills, that they can reflect about themselves and their actions, that they can steer their moods and emotions, that they learn about and overcome their biases, that they are able to weigh personal interests and greater goods. That they can express themselves in a way that allows communication. That they are versed in working with other humans. That they maneuver their own decision making. That they can understand and replicate processes. And that they can assess the quality of highly complex results delivered by an AI and when it is best to re-engineer again.

All of this requires more than skill training. It requires us decision takers and educators in L&D to make sure people nurture their minds and personalities to a point where they can be an adequate companion and opponent to an AI.

Hence, I am convinced that just investing in skill-based training is jumping too short and will actually hamper the digital revolution. Companies are well advised to simultaneously keep funding personal growth and enable their employees to develop self-authorship. So we can find the way forward from today to an integrated human-AI future, that truly creates value.