Month: May 2026

It is a pattern that repeats itself every Monday morning in hundreds of Dutch organizations. A group of employees returns to the workplace after a two-day soft skills training, full of new insights and good intentions. Three weeks later, there is little evidence of this in their behavior. Not because they did not want to, not because the trainer was bad. But because we have known since 1885 that the brain does not learn that way, and the type of training we organize has hardly changed despite that knowledge.

That sounds like a bold statement. It is not just an opinion. It is what cognitive psychology has repeatedly shown, and what in 2015 was once again thoroughly replicated by two researchers from the University of Amsterdam. We have known for almost a century and a half how learning sticks, and how it fades away. And yet the vast majority of soft skills training still relies on the opposite principle: one-time, intensive sessions after which people ‘just have to apply it’.

Microlearning for soft skills is all about that. Not by learning less, but by organizing it differently. Short practice sessions, spread over time, close to the moment of application. That sounds simple, but it requires tools that simply did not exist until recently.

Ebbinghaus’s forgetting curve: a discovery that organizations have hardly processed

Hermann Ebbinghaus, a German psychologist, conducted an experiment in the 1880s with himself as the only subject. He memorized lists of meaningless syllables and tested at various intervals how much he had retained. The curve that resulted from this has become one of the most well-known graphs in psychology and one of the most ignored in the world of corporate training.

The finding was shockingly simple. Within an hour of learning, Ebbinghaus had already forgotten more than half of what he had learned. Within 24 hours, about 70 percent had disappeared. What remained then leveled off at a low level that did not increase without repetition. He called this the ‘forgetting curve,’ and he demonstrated that the pattern was inevitable unless you repeated at specific times.

In 2015, the Dutch researchers Jaap Murre and Joeri Dros from the University of Amsterdam thoroughly replicated this experiment. Their study in PLoS ONE confirmed the original findings of Ebbinghaus, with modern methodology and experimental control. The curve is correct and the pattern is universal. And it says something uncomfortable about how most organizations organize their training.

Because what is a typical two-day soft skills training if not an attempt to pack as much information and practice as possible into 16 hours, only to then let those people go without structured repetition? According to science, that is approximately the least effective way to make something stick permanently.

The spacing effect: why distribution does more than intensity

In addition to the forgetting curve, there is a second finding that argues even more strongly for microlearning. The so-called “spacing effect”; the fact that the same amount of learning time, spread over multiple moments, leads to better retention than spending that same time all at once.

The most well-known evidence for this comes from a meta-analysis by Nicholas Cepeda and colleagues, who in 2006 combined the results of 184 scientific articles, together accounting for 839 independent measurements. The conclusion was clear: spaced learning leads to significantly better retention than intensive learning, almost regardless of the subject. And the effect is no small correction. For some types of material, retention doubles when the same learning time is spread over shorter blocks.

What this means for soft skills training is fundamental. A two-day training on giving feedback, no matter how well designed, can never achieve the same durability as the same 16 hours, spread over 32 half-hour sessions, distributed over a year. Science has been clear about that for almost twenty years. Practice seems to lag behind.

The question of why that is has a simple answer: until recently, there was no practical way to make that kind of distributed practice logistically possible. Booking a trainer three times a month for a half-hour session with four participants

doesn’t work. Hiring a coach for weekly short sessions with each employee is unaffordable. The idea was fine, but the infrastructure was lacking.

Why Soft Skills Are Particularly Susceptible to the Transfer Problem

Microlearning is more effective than intensive sessions for all types of subject matter, but for soft skills, the difference is particularly pronounced. This has to do with the very nature of soft skills: they are not facts to be memorized, but rather behaviors that one must be able to demonstrate in a wide variety of situations—and often at critical moments. Moreover, these situations frequently occur under pressure, or require an ad hoc response with no time for reflection.

Providing feedback to a colleague who has just made a mistake, remaining calm during a conversation that is escalating, or handling resistance without becoming defensive oneself—these are not merely items of knowledge. They are skills whose successful execution depends on self-regulation, practice, and routine. And it is precisely these skills that call for what psychologists term “deliberate practice”—a concept popularized by K. Anders Ericsson: focused, repetitive practice targeting specific aspects, accompanied by immediate feedback on one’s own actions.

What a two-day training course typically provides is a form of introduction; while useful for establishing foundational concepts, it is wholly insufficient for developing the ability to exhibit specific behaviors under pressure. Furthermore, the impact of such training is susceptible to the “illusion of competence.” By the second day of training, everyone feels more proficient than they did on day one; everyone believes they have now mastered the material. Yet it is precisely this overestimation that makes the subsequent regression—typically occurring after three weeks—all the more painful, and all the more demotivating for those wishing to attempt the learning process once again.

Consequently, soft skills—to a greater extent than other competencies—require something that traditional training methods fail to provide: a continuous rhythm of brief practice sessions, situated closely within the actual context of application, and accompanied by objective feedback. In other words: they require microlearning-based soft skills training, rather than standalone training days.

What Microlearning Is—and What It Isn’t

“Microlearning” is a term that has been widely embraced by the L&D sector in recent years—and, as a result, has also become widely diluted. For many organizations, microlearning has now come to mean short, five-minute instructional videos, an interactive quiz, or a daily “learning nudge” delivered via Teams. While not without value, this does not constitute microlearning in the sense intended by academic research.

What distinguishes microlearning for soft skills is that it is not about transferring information in small doses, but rather about practicing in small doses. A five-minute video on active listening is not practice; it is merely a shorter lecture—a transfer of knowledge. True microlearning for soft skills consists of a brief session in which an individual actively demonstrates a specific behavior, receives feedback on it, and has the opportunity to immediately try again. This represents a fundamentally different mechanism.

For organizations serious about soft skills training, this entails a re-evaluation of what “micro” actually implies. It is not about shrinking training content down into bite-sized pieces; rather, it is about increasing the frequency of practice through short, practical simulations that fit seamlessly into the daily work rhythm—whether that means five to ten minutes before a meeting, fifteen minutes on a Saturday morning, or a brief moment just before a difficult conversation.

The technological infrastructure required to make this possible has only recently become available. This also explains why microlearning for soft skills—despite the overwhelming scientific evidence supporting it—remains a relatively nascent concept in actual practice.

How AI Role-Playing Enables Microlearning for Soft Skills

This is where PractAIce comes in. The platform is built upon the very principle that cognitive psychology has advocated for over a century: short, spaced practice sessions within realistic scenarios, accompanied by immediate feedback on one’s own behavior. What was logistically impossible in traditional training is now made possible through the combination of AI avatars and customizable scenarios.

On a Tuesday morning, a manager can spend ten minutes practicing a feedback conversation with an AI avatar that responds just as a real employee would. A week later, they can do it again with a different scenario. A few days after that, they can try a variation involving greater resistance. The forgetting curve is disrupted—not by lengthy training sessions—but by brief, repeated moments occurring at the precise intervals identified by scientific research.

The results align with what research predicts. Skills that would otherwise take dozens of hours of coaching to develop can now be systematically built into a regular work schedule. An employee who devotes fifteen minutes each week to a role-playing exercise gains more practice in a single year than most colleagues do in their entire careers. And most importantly: this practice aligns with how the brain learns, rather than with how schedulers plan.

For L&D professionals, PractAIce adds a dimension that traditional microlearning lacks: measurability at the behavioral level. For every practice session, the platform generates data on an individual’s performance regarding specific competencies—for instance, the specificity of their feedback, how they handled emotions, or how they structured the conversation. This data, collected over weeks and months, reveals a team’s developmental trajectory in a way that was previously impossible.

Frequently Asked Questions about Microlearning and Soft Skills

What exactly is microlearning?

Microlearning is a form of learning in which short, focused learning moments are distributed over time, rather than concentrated into long sessions. For soft skills, this translates to short practice sessions—lasting five to fifteen minutes—conducted repeatedly, featuring varied scenarios and immediate feedback. It differs fundamentally from “short instructional videos”: with microlearning, the emphasis lies on active practice, not passive consumption.

Can you really develop soft skills in short sessions?

Yes—and scientific research even suggests that doing so is more effective than using long sessions. The crucial element is not the duration of a single session, but rather its frequency and how it is distributed over time. Ten fifteen-minute sessions spread out over a month consistently yield more lasting change than two consecutive days of training. This holds even truer for soft skills than for acquiring factual knowledge, as behavioral change relies even more heavily on repeated application.

How often should microlearning take place to be effective?

Research into the “spacing effect” suggests that the optimal frequency depends on how long the material needs to be retained. For skills you wish to maintain continuous mastery of, a frequency of one to three times per week works well. What matters more than the exact frequency, however, is consistency. A weekly practice session that is sustained over time is more effective than a daily session that is abandoned after just two weeks.

Does microlearning replace traditional soft skills training?

Not entirely, but it does shift where the primary value lies. Traditional training remains valuable for initially introducing a topic, establishing a shared vocabulary within a team, and discussing complex situations that require human nuance. Microlearning fills a gap that traditional training could never quite bridge: the structured practice required to translate knowledge into actual behavior. The combination is stronger than either component alone.

Does microlearning work for leadership and management as well?

That is precisely where it works particularly well. Leadership skills—switching between styles, handling resistance, conducting difficult conversations—are exactly the type of skills that develop most effectively through short practice sessions. A manager who spends ten minutes each week practicing a challenging conversation with an AI avatar will, over the course of a year, build a behavioral repertoire that is simply unattainable through traditional training.

In Conclusion

The science surrounding how people learn and forget is not a new discovery. Ebbinghaus conducted his experiments at a time when people were still cooking on coal stoves. These principles have been repeatedly confirmed—most recently by Dutch researchers. The spacing effect is one of the most robust findings in cognitive psychology. Anyone who takes soft skills training seriously can no longer afford to ignore these insights.

Until recently, what was missing was the infrastructure to put these insights into practice. Organizing short practice sessions—spaced out over time, featuring immediate feedback and realistic scenarios—was simply not scalable within most organizations. This is precisely what AI role-playing changes. It is not merely a futuristic pipe dream, but a concrete, readily available method for aligning soft skills training with the way the human brain actually learns.

Wondering how microlearning for soft skills training would work in your organization? A demo of PractAIce takes just fifteen minutes to show you how a short practice session unfolds and the type of developmental data the platform accumulates over time.

If you were to request the personnel administration records of a random Dutch organization, you would receive a list of names and job titles. Senior Consultant. Operations Team Lead. Junior Account Manager. It is so commonplace that we barely stop to think about it, but job titles have been the primary organizing principle of work for the past hundred years. Who you are within an organization is largely determined by what is printed on your business card.

And that exact principle is now under pressure from a generation that fundamentally views it differently. Gen Z, the generation born roughly between 1995 and 2010, is the first generation in the workplace that no longer sees the vertical ladder as self-evident. And that has much deeper consequences for competency-based work than most organizations realize.

This is not another “Gen Z is different” argument. It is an observation about what is actually shifting underneath that discussion: from a work model centered around roles and titles to a work model centered around what people can do, what they want, and what they want to develop. For L&D professionals, this is not some distant future. It is happening now.

What the data shows and why the bookshelf is starting to wobble

It is tempting to dismiss Gen Z’s behavioral shift as generational complaining. The problem is that the data is becoming increasingly consistent. Only 6% of Gen Z identifies reaching a senior leadership position as their primary career goal, according to Deloitte’s Global 2025 Gen Z and Millennial Survey. At the same time, learning and development consistently ranks in the top three reasons they choose an employer. They want to grow, just not necessarily upward (vertically).

What this reveals is something more fundamental than a shift in ambition. Gen Z has implicitly realized that vertical promotion is becoming less predictive of what work actually is. The role “team leader” means something entirely different in ten different organizations. A senior title says little about what someone can actually do in 2026, considering how quickly work itself changes. And a career plan like “in five years I want to be X” rarely matches the reality of what someone is actually doing five years later.

The World Economic Forum confirmed this in its Future of Jobs Report 2025: 39% of employees’ current skills will be transformed or outdated by 2030. In essence, that means a complete renewal of workforce skills every decade. A job title is not flexible enough to keep pace with that speed, but a competency profile is.

The quiet shift toward competency-based work

What Gen Z is intuitively doing is now being structurally organized by forward-thinking companies. It is called the “skills-based organization,” or in Dutch terms: competency-based work. The idea is simple in theory, complex in execution: stop organizing around roles and start organizing around competencies. Instead of an org chart where people are locked into fixed roles, organizations become dynamic networks where people are deployed based on what they can do, and where development focuses on the competencies they want to build.

Deloitte’s own research calls this “a portfolio of ways to organize work, enabling greater agility and more meaningful packages of work.” It sounds abstract, but the impact is concrete: internal mobility moves faster, talent is used more effectively, and employees stay longer because growth is no longer tied to an empty chair above them. The World Economic Forum even stated that skills-based hiring works for jobs that do not yet exist, because the focus shifts from what someone was to what someone can become.

For organizations making this transition, a paradox emerges. On one hand, it delivers strategic advantages leadership teams love: agility, retention, and better use of talent. On the other hand, it requires something most organizations are not prepared for: infrastructure that makes competencies visible, trainable, and measurable. Without that infrastructure, “skills-based” remains a nice phrase on a strategy slide rather than a reality on the work floor.

The problem L&D now has to face

This is where things become uncomfortable for L&D professionals. Most learning and development programs in Dutch organizations are still organized around roles, not competencies. A training offer is called “Leadership for New Managers,” not “Giving feedback to defensive team members.” A training catalog is usually a list of courses, not a map of interconnected competencies.

The result is that training remains an event tied to a role transition, rather than an ongoing process connected to the competencies someone wants to develop at a specific moment. For a Gen Z employee who wants to grow without necessarily becoming a manager, that offering feels irrelevant. For an organization aiming to work competency-first, it lacks the actual building blocks.

What is missing is what researchers from the World Economic Forum call a “Global Skills Taxonomy” for the individual organization: a shared overview of which competencies matter, how they connect, how they are developed, and how growth can be observed. Not as a bureaucratic instrument, but as an operational framework for recruitment, development, and internal mobility. Many organizations start building this but run into a deeply practical issue: how do you make soft skills competencies visible at all?

Soft skills competencies: making visible what has always been intangible

This is the heart of the challenge. For hard competencies, such as mastering a programming language, writing an Excel formula, or giving a presentation in English, there are ways to demonstrate proficiency. A test, a project, a certificate. But for the competencies growing fastest in Future of Jobs rankings — think effective communication, handling resistance, situational leadership, or conflict management — reliable measurement tools have long been missing.

That is not accidental. Soft skills competencies are contextual. Someone can be brilliant at giving feedback to a peer and completely freeze in a conversation with a defensive executive. Someone can remain calm in a meeting and escalate emotionally in a one-on-one conversation. A single snapshot says very little; you need to see how someone behaves across different situations to reliably assess competency.

Until recently, this meant: 360-degree feedback, manager observations, peer review. All valuable, all labor-intensive, and none scalable enough to support competency-based work across an entire organization. It is exactly this gap where AI training and AI roleplay introduce something fundamentally new. Not as a gimmick, but as infrastructure for the competency-based work model Gen Z already expects.

How AI roleplay makes competencies visible and trainable

PractAIce connects directly to this challenge. The platform allows employees to go through conversational scenarios with an AI avatar that responds the way a real colleague would. For example in feedback conversations, conflict situations, or negotiation moments. What this changes is not the content of training, but its structure. Instead of isolated role-based training sessions, organizations create an ongoing practice environment centered around competencies.

An employee who wants to improve feedback skills can practice across a range of scenarios that reveal the complexity of that competency. Someone focused on situational leadership can move through scenarios where different leadership approaches are appropriate. The scenario aligns with the employee’s development goals, not the schedule of an external training provider.

And perhaps just as importantly, PractAIce generates behavioral-level data from every practice session. How specific was the feedback? Was enough space given to the other person? How was defensiveness handled? That data, collected across weeks and teams, creates something that previously did not exist: a reliable measurement system for soft skills competencies that does not depend on self-reporting or a manager’s temporary impression. For a competency-based organization, that is not a luxury — it is a requirement.

It also matches the learning rhythm Gen Z expects. Short practice sessions, completed when convenient, with immediate feedback. Not a yearly training event, but continuous micro-moments in which competencies gradually develop. That is not a “Gen Z adjustment”; it is how the brain actually learns. Gen Z just happens to be the first generation demanding it explicitly.

What L&D can do now without turning everything upside down

The transition to competency-based work does not need to be a big-bang transformation. What helps is starting with three concrete shifts, each valuable on its own and together capable of moving something much deeper.

The first shift is linguistic: stop talking in roles and start talking in competencies. In development conversations, performance reviews, and job descriptions. Not “I want to become senior,” but “I want to improve my ability to handle difficult conversations.” At first that language feels forced, but within months it changes how people think about growth.

The second shift is structural: create explicit learning paths for the most critical soft skills competencies, separate from roles. A learning path for giving feedback that applies equally to a team lead, an individual contributor, and a director. Tools like PractAIce make this scalable by adapting scenarios to the user’s level and context.

The third shift is measurable: introduce competency data into development conversations, not as an evaluation tool, but as a growth tool. Not “how are you scoring?” but “can you see where you are improving and where refinement is possible?” The shift sounds small, but it fundamentally changes how employees view their own development. And it aligns perfectly with Gen Z’s existing relationship with data about sleep, fitness, and personal habits.

Frequently asked questions about competency-based work

What is the difference between competency-based work and role-based work?

Role-based work organizes people around positions with fixed responsibilities and tasks. Competency-based work organizes people around their skills, mindsets, and development potential. The difference is not just terminology but emphasis: in a competency-based organization, someone can contribute in multiple ways based on what they can do, rather than what their title allows. For internal mobility, talent retention, and organizational agility, that is a fundamentally different way of working.

Does competency-based work also function in traditional industries, or only in tech companies?

The principles work everywhere, but the implementation differs. In highly regulated sectors such as healthcare, education, and government, job titles remain formally important, but competency-based work can coexist in how development, mobility, and evaluation are organized. It does not require a complete restructuring; it can function as a layer on top of the existing structure.

How do you reliably measure soft skills competencies?

The weakest method is self-reporting; asking someone “are you good at giving feedback?” produces little useful data. Stronger methods include 360-degree feedback and structured observation by managers, but those are labor-intensive and highly dependent on specific moments. AI roleplay adds a third layer: standardized behavioral observation in scenarios that genuinely challenge the competency, measured across multiple practice sessions. That creates a richer picture than any single method alone.

How does AI training fit into a competency-based organization?

AI training works best as infrastructure for competency development, not as a standalone solution. PractAIce makes it possible to build practice pathways for specific soft skills competencies — such as effective communication, handling resistance, or situational leadership — that demonstrate development over time. Training then becomes part of the rhythm of work itself, not a separate event category.

In conclusion

The end of the job title sounds more dramatic than it actually is. Job titles will continue to exist; they are practical, legally embedded, and culturally ingrained. What is changing is their position as the primary organizing principle. For the generation now entering the workforce, and increasingly for the organizations trying to attract them, the key question is no longer what someone is, but what someone can do and wants to develop.

For L&D professionals, this is an invitation to rethink the foundations of the profession. Not to tear everything down, but to build the infrastructure that truly enables competency-based work: a shared language of competencies, learning pathways independent of roles, and data that makes behavioral development visible.

Would you like to explore how PractAIce could fit into your organization as infrastructure for competency-based work? A demo shows in fifteen minutes how a practice session works and what kind of competency data the platform builds over time.

Until around 1820, almost nobody learned anything through a course. Anyone who wanted to make shoes became an apprentice to a shoemaker. Anyone who wanted to work with metal worked alongside a blacksmith. Anyone who wanted to learn writing did not mainly read about writing, but sat next to someone who actually did it. The system was called “master and apprentice,” and it worked so well that it was independently invented in nearly every civilization. For centuries, it was the most natural way for people to acquire craftsmanship.

That system has largely disappeared from the modern working world. Not because it worked worse than what replaced it, but because it was not scalable to the new industrial reality. A master could guide one or two apprentices, not thousands of employees. We compensated for that with courses, books, education, and later with training programs. And we silently accepted that, for modern and complex skills, there would never again be a master standing beside you while you did the work.

That is exactly what is changing now. AI coaching is not a break from the way we learn; in a sense, it is a return to it — only on a scale that would have been unimaginable in 1820. And for soft skills training, that means something fundamental.

What we discovered when we took another look at learning in practice

In 1989, three scientists investigated why people in the past often learned faster and better through practice. Their conclusion was simple: people learn far more effectively when someone is beside them to demonstrate, observe, correct, and help in the moment itself. Not just explanation beforehand, but guidance during the actual doing. They later gave this way of learning the name “cognitive apprenticeship.”

What they uncovered was that a good master did six things that rarely come together in modern instruction: demonstrating (modeling), guiding and correcting during execution (coaching), providing temporary support (scaffolding), encouraging the learner to explain their thinking (articulation), stimulating reflection, and ultimately creating space for independent experimentation. According to Collins and his colleagues, it is precisely the combination of these six elements that makes the difference between superficial learning and lasting learning.

What fascinated them most was why this model was so rarely applied in practice. The answer lay in scale: a teacher cannot treat a class of 30 students the way a shoemaker treats a single apprentice. As a result, the form of education lagged behind what we already knew to be more effective. For soft skills, the gap between what we knew and what we actually did was even greater: how do you simulate a master standing beside you during a difficult conversation when that master also has their own work to do in the evening?

Situated learning: why learning depends on context

Around the same time, John Seely Brown, Allan Collins, and Paul Duguid developed a related idea that became known as “situated cognition.” Their argument — which sounded radical in 1989 but is now considered almost mainstream — was that knowledge and context are inseparably connected. Learning something in a classroom and applying it in the workplace are not two phases of the same process; they are two different learning processes.

Their famous formulation stated that “situations partially produce knowledge through activity.” In other words: what you learn is partly shaped by where you learn it. Someone who learns conflict management through a role-play exercise with a colleague in a training room learns something fundamentally different from someone who learns it during a real conversation with a frustrated customer. Not because the content is different, but because the context causes the brain to encode it differently.

For soft skills, this has an uncomfortable implication. The skills you practice during a training day are difficult to transfer to the workplace because the workplace is a different context from the training room. That does not mean the training was of poor quality, but rather reflects a fundamental characteristic of how learning works. It explains the transfer problem that L&D has struggled with for decades: not because trainings are ineffective, but because they miss one crucial element — proximity to the real context of execution.

It is exactly what that old way of learning did have. People did not practice in a separate space, but in the same context in which the real work took place. The result was craftsmanship that lasted, because learning and doing were never separated from one another.

What AI coaching now makes possible

This is where two developments come together that are each interesting on their own, but together create something entirely new. AI is capable of simulating realistic conversation scenarios in which behavior — not just knowledge — can be practiced. And that same AI is available at the moments when a human mentor never could be, for example at 7:30 in the morning before a difficult meeting or at 10 o’clock at night after a day in which something went wrong.

Voor het eerst sinds we praktijkleren hebben vervangen door klassikaal leren, kunnen we de principes achter die oude leervorm opnieuw toepassen, maar nu op een schaal die vroeger onmogelijk was. AI-coaching maakt dat mogelijk. Het kan tijdens de oefening bijsturen. Het kan ondersteuning afbouwen naarmate iemand vaardiger wordt. Het kan de leerling laten verwoorden wat ze deed en waarom. En het kan dit doen voor honderden medewerkers tegelijk, zonder dat de kwaliteit per oefening daalt.

Importantly, AI coaching does not replace a human coach or mentor. Just as the master in 1820 was not replaced by a textbook, AI does not replace the human nuance, life experience, and wisdom that a good coach provides. What AI does offer, however, is something that had largely disappeared from the modern workplace at scale: direct, contextual practice with immediate feedback, available at the moment it matters most.

Why this is the biggest change in soft skills training in a hundred years

For hard skills, we have had effective learning structures for quite some time. You learn programming by writing code and seeing it work or fail. You learn English grammar by writing sentences that a corrector reviews. The feedback loop is fast, and the result is immediately measurable.

For soft skills training, this was fundamentally different until recently. Someone could spend hundreds of hours in training about giving feedback and only discover in practice that they still could not do it effectively. The feedback loop was often delayed rather than immediate, sometimes taking days or weeks instead of minutes. That is one of the reasons why soft skills, despite decades of training, have not structurally improved in most organizations.

AI training with realistic avatars changes that dynamic completely. A manager can practice a feedback conversation twenty times before having it in real life. They can experiment with openings, wording, and different ways of handling resistance. And after every attempt, they receive immediate, behavior-specific feedback. This is not an incremental improvement over traditional training; it is a fundamentally different learning process, much closer to the way the brain actually develops skills.
PractAIce is built around exactly this principle. The AI avatar is not just a conversation partner; it is a partner that operationalizes the six elements of cognitive apprenticeship. The platform demonstrates what effective behavior looks like, provides scaffolding for beginners, offers explicit reflection after every exercise, and gradually reduces support as the user gains mastery. That is not accidental. It is built on four decades of learning science.

What this means for L&D professionals

The practical implication is that the role of L&D within organizations is shifting. No longer merely the organizer of training sessions, but the architect of learning infrastructure. No longer simply the booker of trainers, but the builder of practice pathways. No longer dependent on one-time interventions, but responsible for continuous development in the flow of work.

That requires different questions at the start of a learning journey. Not “which training fits this role transition?”, but “which competencies do we want to develop, and how do we build a practice structure that operationalizes the six elements of cognitive apprenticeship?” That may sound academic, but in practice it is surprisingly practical. Especially with platforms that can do the kind of work a human mentor simply cannot sustain for hundreds of employees at the same time.

The beauty of this shift is that it does not require replacing everything that already exists. Traditional training remains valuable for introducing knowledge and creating a shared language. Coaching remains essential for human nuance. What AI coaching adds is the practice infrastructure in between — the part where most behavioral change actually takes place, and which until now has simply been missing in most organizations.

Frequently asked questions about AI coaching and the future of learning

What is the difference between AI coaching and e-learning?

E-learning is, at its core, the transfer of information in digital form: videos, modules, quizzes. The brain consumes the material, but does not practice behavior. AI coaching is fundamentally different: it is interactive, scenario-based, and focused on behavioral change. Not learning about giving feedback, but actually giving feedback and receiving immediate responses to it. That difference explains why AI coaching has a much stronger impact on soft skills than traditional e-learning ever could.

Does AI coaching replace human coaches?

No. They serve different functions. A human coach provides context, life experience, and intuition about what is happening beneath the surface — things AI cannot replicate. AI coaching provides scalable practice opportunities with immediate feedback on specific behaviors, something a human coach could never sustain for hundreds of employees. The combination is stronger than either on its own: human coaching for strategic conversations, AI training for continuous practice.

How does the brain actually learn soft skills?

Not by reading or listening about them, but through application. Soft skills are behavioral patterns, and behavioral patterns develop through repeated execution combined with feedback. Cognitive psychology has been clear about this for more than a century. What is new is that we now have an infrastructure that makes this repetition possible without depending entirely on a human coach — and that opens possibilities that simply never existed for most organizations.

Does AI coaching fit every role, or mainly leadership?

It works especially well for leadership, because leadership skills depend heavily on switching between styles under pressure. But its application is much broader: customer-facing roles, sales, healthcare, and any function where conversational ability shapes performance. What determines its relevance is not the seniority of the role, but whether it involves soft skill competencies that can only be developed through practice.

In conclusion

The history of learning is long, and most shifts within it have been relatively small. What we are experiencing now is bigger than a passing trend. For the first time in two centuries, we can once again make the form of learning that has always been the most effective — direct practice with a master standing beside you — available at the scale required in the modern workplace.

This is not a solution to everything. It requires thoughtful implementation, realistic expectations, and a clear understanding of what AI can and cannot do. But for the first time, it opens the possibility of approaching soft skills training in the way learning science has long prescribed: not as an event, but as a practice; not as knowledge transfer, but as behavioral development; not as an annual workshop, but as a continuous learning process.

If you would like to explore how AI coaching through PractAIce could work within your organization, a demo can show in fifteen minutes how a conversation with an AI avatar works — and provide a far more concrete impression than any description ever could.

Ask ten managers which leadership model they are most familiar with from a training course, and nine will mention the Hersey-Blanchard model of situational leadership. The four quadrants of directing, coaching, supporting and delegating have become so familiar to many managers that they can sketch them from memory in a meeting. The model is the most widely used framework in leadership development worldwide, and for good reason: it is intuitive, practical, and contains a truth that is confirmed time and again in practice.

And yet, research consistently shows that the very same managers who know the model by heart almost always fall back on one or two preferred styles in their day-to-day work, regardless of what the situation or the employee actually requires. This is not because they do not understand the theory, but is often explained by the difference between knowing and being able to do.

That difference is precisely where most leadership training programmes fall short. And it is also precisely where new forms of practice, such as AI role-plays, can play a role that traditional programmes never fulfilled.

The Hersey-Blanchard model and why it endures

Paul Hersey and Ken Blanchard published their model of situational leadership in 1969, at a time when the prevailing view was that good leaders possessed a fixed set of characteristics – that leadership was a trait, not a skill. Their fundamental insight was different: effective leadership is contextual. What works for a new employee does not work for an experienced professional. What works in a crisis does not work in a stable situation.

The model that emerged from this has four styles, linked to four levels of employee development. A new team member who is enthusiastic but inexperienced requires a directive style: making it clear what needs to be done, how and when. An employee who is becoming more skilled but feels insecure requires coaching: more scope for independent thinking, but still with guidance. An experienced employee experiencing a dip in motivation requires support. And a high-performing, motivated professional requires delegation and the freedom to take the initiative.

The model has been tested, criticised, revised and expanded in the years since. Recent studies show that the model is still widely researched and applied, and that the main point of criticism is not the theory itself, but the difficulty managers face in applying it consistently in practice.

The real problem: the gap between knowing and doing

This is where things get uncomfortable for those who invest heavily in leadership training. Research analysing managers’ actual behaviour – not what they say they do, but what they actually do – shows that the majority of managers fall back on a single dominant style in 70 to 90 per cent of their interactions. Usually, this is the style in which they feel most comfortable, not the style the employee needs at that moment.

This is not a matter of unwillingness. It is how the brain deals with quick decisions under pressure. In a meeting, in a corridor chat, in a performance review where time is short and tension is high, everyone falls back on the most practised patterns. And if those patterns have formed around a single style – often a directive one, sometimes a coaching one, rarely all four flexibly – then the model remains a poster on the wall rather than lived practice.

This explains another persistent pattern. Employees who evaluate their manager are far more likely to say they feel inadequately supported or, conversely, overly micromanaged, than their manager themselves realises. Recent meta-analytical work on situational leadership confirms this discrepancy between managers’ self-perception and their teams’ experience. Not so much because managers are mistaken, but because they fail to see the difference between their preferred style and the desired style without an external mirror.

Why traditional leadership training often still fails to address this adequately

A typical leadership training course on situational leadership follows a familiar pattern. A day or two, with theory, group exercises, and a concluding reflection session. Participants go home with new insights, a nice workbook, and the sincere intention to make their style more flexible.

And then Monday begins. The issues of the day take over. The first meeting goes as usual. The first difficult employee is dealt with in the usual way. And within a few weeks, the manager is back in the same patterns they had before the training. This has nothing to do with the quality of the training, but rather with the well-known transfer problem, which manifests itself here in full force.

There is something unique about leadership. The skills you are trying to develop—such as switching between styles, understanding what an employee needs at a specific moment, or setting aside your own preferences when the situation calls for something different—are precisely the skills that can only be developed through repetition. Research into expertise development, particularly the work of K. Anders Ericsson on deliberate practice, shows time and again that this type of skill requires hundreds of hours of focused practice, not just one or two days.

That is also why the most effective leadership development programmes we know of – such as long-term coaching programmes, mentoring, and structured reflection practices – have never been truly scalable. They work, but they are expensive and labour-intensive. For a large proportion of organisations, this meant sticking to two-day training courses and hoping for the best.

What AI role-playing adds to leadership development

This is where it gets interesting, and this is where PractAIce comes in. The platform allows a manager to run through the same situation multiple times, with variations in how the employee reacts. A conversation with a high-performing employee who suddenly seems less motivated. A conversation with a new team member who is clearly overwhelmed. A conversation with an experienced professional who is resisting change.

In each of these scenarios, the manager is given the opportunity to try out different styles and experience their effect immediately. What effect does a directive approach have on a professional who is actually seeking more autonomy? How does an insecure team member react to delegation? Switching between styles thus ceases to be a theoretical skill, but becomes an internalised repertoire that builds up through repetition.

Importantly, the scenarios can be adapted to the specific organisational context. A manager in a production environment practises with different situations than a team leader in a knowledge-based organisation or a manager in the healthcare sector. PractAIce makes it possible to build scenarios around the specific team dynamics and conversation styles that occur in one’s own work practice.

For L&D professionals, the platform adds something else that is crucial: measurability. For each practice session, the system records which leadership style was used, how effective it was in that scenario, and how a manager’s repertoire of styles develops across multiple practice sessions. This provides, for the first time on this scale, insight into the actual flexibility of leadership within an organisation, based on observed behaviour.

Frequently asked questions about situational leadership

What is the difference between situational leadership and coaching leadership?
Coaching leadership is one of the styles within the broader model of situational leadership. It is characterised by asking questions, giving space and supporting independent thinking, and is very effective with employees who have the basic skills but are still unsure about how to apply them. Situational leadership posits that coaching is the right style in specific situations, not always. A new employee with insufficient knowledge is more likely to benefit from being guided than from being coached.

Does situational leadership also work in a flat organisation or self-managing
teams?

Does situational leadership also work in a flat organisation or self-managing teams?
Yes, although its application looks different. The basic principle of situational leadership – that different people need different forms of leadership at different times – applies regardless of structure. In self-managing teams, the question shifts from ‘which style suits this employee?’ to ‘what form of leadership does this team need right now?’ Switching between styles remains the key.

How do you know which style is right at any given moment?
The model offers guidelines, but in practice it requires observation. Two things consistently help: looking at the combination of the employee’s competence and motivation for this specific task (not in general), and engaging in a conversation about what someone needs rather than assuming you already know. That observation is itself a skill that develops with practice.

Can you really learn situational leadership through an AI role-play?
It aligns surprisingly well with what the model requires. Learning situational leadership means: practising repeatedly how to switch between styles in different scenarios, with immediate feedback on what worked. That is exactly what AI role-plays make possible. What AI does not replace is the human nuance of an experienced mentor or coach. What it does add is the scalable practice environment that this particular skill requires.

In conclusion

Situational leadership, despite its age, remains one of the most useful models for anyone wishing to develop their leadership skills. Not because it is perfect, but because it reveals a truth that is repeatedly confirmed in practice: there is no single right way to lead, and the art lies in switching between styles.

The question for organisations is not whether this model is still relevant. That has long since been answered. The question is how to help managers make the transition from simply knowing the model to actually switching between styles in practice – even under pressure, even in difficult conversations, and even when time is short. That transition requires something that traditional training does not offer: structured practice.

Would you like to explore how PractAIce can facilitate that practice for your leadership team? A fifteen-minute demo shows how a conversation unfolds and what development data the platform generates.

Ask ten managers what they find most difficult about their job, and you’ll get the same answer remarkably often. Not strategy, not planning, not even meeting targets. What keeps them awake at night is conflict. Between team members. Between themselves and an employee. Between departments that begrudge each other their work. Conflicts that they are either unable to resolve, or avoid for so long that they escalate into something much bigger.

This is remarkable because, unlike financial reporting or project management, for example, conflict management is rarely systematically trained in any organisation. People are appointed as managers on the basis of their professional performance and are simply expected to develop conflict management skills on the side. And yet conflict management is a core competence for every manager. If you do not master it properly, it has immediately noticeable consequences for people on the shop floor.

The cost of this assumption is higher than many organisations realise. And the solution is no more complicated than for other skills: serious practice, in realistic situations, with immediate feedback. The problem is simply that traditional training rarely addresses this. The daily work context is dynamic, conversations do not go as planned and situations are constantly changing. It is precisely in that reality that you need to be able to apply it, and that is where traditional training often falls short.

The cost of a conflict you don’t address

The cost of a conflict in the workplace is rarely measured directly. It is hidden in delayed projects, in employees who eventually leave, in teams operating at half-capacity because underlying tension has never really been addressed. And in direct working hours lost to navigating conflict rather than working.

The best-known figure on these costs comes from the 2008 CPP Global Human Capital Report. The report found that American employees spend an average of 2.8 hours per week dealing with workplace conflicts, amounting to $359 billion in lost productivity per year. For managers, that figure is higher: according to follow-up research, they spend between 20 and 40 per cent of their time managing conflicts. That is almost a full working week per month.

What is striking in that same report is a second finding that is cited less frequently but is just as telling: almost 60 per cent of employees have never received basic training in conflict management. At the same time, 95 per cent of those who have received such training say it has helped them to navigate conflicts constructively. The figure comes from an American study, but the pattern is similar worldwide.

In other words: most people are confronted with conflict on a daily basis, it costs the organisation significant productivity, training is proven to work, and yet it is overlooked in most organisations.

Why people shy away from conflict (and what it costs them)

One of the most influential models for understanding conflict behaviour is the Thomas-Kilmann Conflict Mode Instrument, developed in the 1970s and used worldwide ever since. The model distinguishes five ways in which people deal with conflict: avoidance, accommodation, compromise, collaboration and competition. No single style is universally good or bad; each has a function depending on the situation.

What the research shows is that the vast majority of employees, including managers, develop a strong preference for one or two styles, and apply them in all situations, even outside of work. The most common preferred style is avoidance. For most people, seeking out conflict feels socially risky, and in uncertain situations the brain opts for the familiar route, even if it proves more costly in the long run.

The problem with avoidance is that it rarely removes the tension. It merely shifts it. An employee who is not challenged on behaviour that irritates the team will continue to exhibit that behaviour, and the team will gradually become more frustrated. A conflict between departments that remains unaddressed leads to silent sabotage rather than productive discussion. Research in healthcare shows that poor conflict management is structurally linked to higher staff turnover, increased absenteeism and poorer outcomes. The pattern extends beyond the healthcare sector.

What makes dealing with resistance effective

Dealing with resistance is not a matter of persuasion. That is a misconception that many management training courses implicitly reinforce. Anyone who tries to overcome resistance by pushing harder usually increases precisely the resistance they wish to remove. That is not a failure of character; it is how the brain works under social pressure.

Research consistently shows that a combination of three elements is more effective. Firstly: a genuine curiosity about what lies beneath the resistance. People rarely object to the decision itself; they object to what the decision means for their position, their work, and their sense of competence. If you fail to explore this, you only see the symptom.

Secondly: acknowledgement without agreement. A manager can take someone’s objection seriously without agreeing with it. The difference is crucial, and it is precisely what many managers overlook in practice, because they fear that acknowledgement is tantamount to giving in. It is not. Acknowledgement is what turns a conversation into a dialogue rather than a one-way street.

Thirdly: clarity about what is and isn’t negotiable. Many conflicts escalate because it’s unclear where the room for manoeuvre lies. Vague wording fuels hopes of influence where none exists, and frustration when that becomes apparent. “I hear your objection and I won’t change the decision, but I am willing to work with you to see how we can make it workable

Why knowledge alone is not enough

Herein lies the core problem of conflict management as a training subject. After a day’s training, virtually all managers understand what they should do. They know the models. They can identify the styles. They understand why genuine curiosity is more effective than persuasion. And yet they fall back on old patterns as soon as the moment actually arrives, as soon as their heart rate rises, the other person becomes more defensive, and the space in their head shrinks.

All of this comes down to a lack of practice. Under stress, the brain reverts to the most practised patterns, even if they aren’t the most functional ones. Building a new repertoire requires repeated exposure to the stressful situation, in a context where the stakes are low enough to allow for learning and high enough to feel realistic.

That is precisely what traditional training does not offer, or offers only briefly. A role-play with a colleague in a group session does not feel like a real conflict. Everyone knows it is just a drill. The tension that makes conflict management so difficult is missing. And the three or four times you practise something in such a setting are far below the number of repetitions needed to change behaviour under stress. Research into deliberate practice shows time and again that skills like these require dozens to hundreds of focused practice sessions, not just three or four.

How AI role-playing makes conflict management something that can be practised systematically

PractAIce fills this gap perfectly. The platform allows employees and managers to practise conflict resolution conversations with an AI avatar that reacts just like real colleagues do: defensively, emotionally, and with escalation when the conversation takes a turn for the worse. Important: the scenario can be tailored to the specific situations within your own organisation. A manager in the healthcare sector deals with different conflicts than a team leader in a sales organisation, and the platform makes that distinction possible.

What sets this apart from traditional training is the scale of the practice. A manager can run through a conflict conversation not three but thirty times, with variations in how the other person reacts. She can try the same opening with different follow-ups. She experiences how a slightly different phrasing results in a completely different conversation. And after each attempt, she receives concrete feedback on what worked and what didn’t. So not in general terms, but based on specific behavioural indicators.

For organisations, this delivers an additional benefit: visibility. For each practice session, PractAIce generates data on how someone handles resistance, whether space was left for the other person, or whether escalation was effectively contained. This data, collected across a team, reveals patterns that would otherwise remain hidden. Not to assess people, but to enable targeted development where you make a real difference.

Frequently asked questions about conflict management

What is the difference between conflict avoidance and conflict management?
Conflict avoidance is shying away from a conversation that really ought to take place. Conflict management is consciously choosing when and how to engage with a conflict. The difference lies in intentionality: avoidance often happens out of habit or discomfort, whilst management is an active choice that takes into account timing, context and purpose.

How do you deal with a colleague who won’t accept feedback?
Often, defensiveness is a sign of something deeper, such as fear, past experiences, or the feeling of not being heard. An effective approach starts by exploring what is going on before you focus on the behaviour again. That does not mean abandoning your position, but rather reversing the order: understand first, then address. It is a skill that develops mainly through practice, not just in theory.

Can you teach conflict management to someone who avoids conflict?
Yes, but it requires a different approach to that used with people who are more willing to engage in conflict. For employees who avoid conflict, gradual exposure works better than an intensive programme. Start with low-risk scenarios in a safe training environment, build up to more challenging situations, and reassure them that failure will have no consequences. AI role-plays are particularly suitable for this group because the barrier to practising is lower than in group training.

What if the conflict is between two employees and not my responsibility?
As a manager, you then have two roles: mediator in the moment, and builder of a team culture in which conflicts are more likely to be brought to the surface. Both are skills. Mediation requires impartiality and clarity; building culture requires consistency in how you yourself deal with tension. PractAIce offers scenarios for both.

In conclusion

Conflict management is a skill we collectively underestimate. We accept that managers simply have to deal with it, whilst it is measurably one of the biggest cost drivers in any organisation. We accept that people learn through trial and error, whilst this very skill benefits from structured practice.

The question is not whether conflict management can be developed. The research is clear on this: training works, provided it allows for repetition in realistic situations. The question is whether your organisation has the infrastructure to make such practice a structural reality, or whether, like so many others, it remains merely an intention.

Would you like to explore how PractAIce builds conflict scenarios around the specific situations in your organisation? A 15-minute demo will give you a concrete idea of this.

There is something strange about giving feedback in the workplace. Everyone says it’s important. Every leadership book devotes chapters to it. Every HR strategy includes a section on feedback culture. And yet, even in organisations that claim to have ‘got it right’, it remains one of the most dreaded moments in working life. People put it off. They say it the wrong way. Or they say it too late, in a formal performance review where the other person should have been prepared long ago.

The underlying assumption is that giving feedback is essentially a good thing. That, as long as you do it, it leads to better performance. That assumption is largely incorrect. And that is not a gut feeling, but a scientifically established finding that still has barely any impact in practice.

Anyone who genuinely wants to improve feedback within an organisation must first understand where it goes wrong. The solution lies not in giving more feedback, but in giving better feedback. Feedback that is specific, behaviour-focused and immediately actionable. And above all: feedback that you keep practising in real life, until it becomes a natural part of how people work together.

The uncomfortable secret of feedback

In 1996, Avraham Kluger and Angelo DeNisi published a meta-analysis in Psychological Bulletin that turned the feedback literature on its head. They examined hundreds of results from years of research into feedback and reached a sobering conclusion. On average, feedback did indeed lead to an improvement in performance, but in more than a third of all cases, giving feedback actually led to a deterioration in performance. That is no minor deviation. It is a fundamental phenomenon that most managers are unaware of.

What Kluger and DeNisi uncovered is that feedback is not a neutral intervention. The way it is given, at what point, by whom, and focused on which level (the task, the self, or the process) determines whether it helps someone progress or actually hinders them. Feedback focused on the recipient’s self, for example: ‘you are too detail-oriented’, is more likely to lead to defensiveness and reduced performance than feedback focused on the task. For example: ‘this email lacks a clear question in the first paragraph’.

That distinction may seem minor, but in practice it makes a huge difference. And it explains why organisations that ask their managers to ‘be more direct’ sometimes end up with worse results than before. And not so much because directness is wrong, but because directness without skill leads to precisely the kind of feedback that the meta-analysis has already identified as detrimental to performance.

Why feedback goes wrong: three mechanisms we underestimate

There are three patterns that repeatedly undermine feedback in the workplace, and none of them has anything to do with the content of what is said.

The first is timing. Research shows that feedback given closer to the moment of action is consistently more effective than feedback given weeks later. And yet the standard model in most organisations is exactly the opposite: annual appraisal interviews with observations accumulated months ago. An employee who made a mistake in March is told in November that they should have done better. The brain has long since filed that situation away as closed, and the feedback comes across as a criticism of who someone is rather than what they did.

The second is specificity. General feedback (“you need to show more initiative”) gives the recipient no starting point for changing their behaviour. Specific feedback (“in Tuesday’s meeting, you waited until three colleagues had spoken before making your point; I’d like to hear from you sooner”) does. The difference lies not in how it sounds, but in whether you can actually do anything with it. In other words: concrete behaviour.

The third is reciprocity. In organisations where managers give feedback but never ask for it themselves, a dynamic arises that psychologists consistently link to a reduction in trust and openness. Research in the Harvard Business Review shows that 57% of employees would rather receive corrective feedback than purely positive feedback, whilst managers are actually reluctant to give that feedback. That gap between what people want and what they get is one of the weakest points in most feedback cultures.

What constructive feedback actually does to the brain

To understand why constructive feedback works and ‘bad’ feedback does not, it helps to look at the brain. When someone receives feedback that is interpreted as an attack on the self, this activates the amygdala, the area of the brain responsible for the fight-or-flight response. At that moment, the prefrontal cortex’s capacity to process and integrate information is reduced. In other words: just when you want someone to learn, the brain shuts down to learning.

This is no excuse for giving vague feedback or avoiding difficult messages. It explains why a specific approach is needed. Giving constructive feedback means: sticking to the substance, but choosing the form in such a way that the recipient is actually able to take in what you are saying. That requires skill, situational leadership and practice.

What often works in practice is a structure that anchors the feedback in specific behaviour, identifies its effect, and invites dialogue about alternatives. Models such as COIN (Context, Observation, Impact, Next steps) or the simple situation-behaviour-impact format help with this. But as with all skills, knowing the model is the easy part. Applying it, whilst your heart rate rises and the other person becomes more defensive, requires something fundamentally different.

Why training on giving feedback rarely leads to different behaviour

An average feedback training programme lasts a day, sometimes two. Participants learn models, practise once or twice in a role-play with a colleague, are given a handout, and return to work. Three weeks later, a team lead is sitting down with a colleague who is missing deadlines, and without exception falls back on the patterns they had before the training. Not because the training was poor, but because a single session of practice is not enough to change behaviour.

This is the transfer problem faced by the entire L&D sector. Research estimates that less than ten per cent of what is learnt in training actually translates into new behaviour in the workplace. For feedback skills, that percentage is likely even lower, because application depends so heavily on factors such as the conversation partner, the context and emotional self-regulation. And when we talk about emotional regulation, people often forget that this is only developed through repeated exposure.

Psychologist K. Anders Ericsson demonstrated in his research on expertise development that skills such as giving feedback do not arise from insight or motivation. They arise from deliberate practice: focused, repeated practice on specific aspects, with immediate feedback on one’s own actions. That is precisely what cannot be offered in a single day of training, and also what most organisations were unable to organise until recently.

How AI role-plays measurably improve feedback

This is where PractAIce comes in. The platform allows employees to practise feedback conversations with an AI avatar that reacts just as a real colleague would – with defensiveness, with emotion, and with unexpected counter-questions. That sounds simple, but it fundamentally changes how feedback skills develop.

A manager preparing for a difficult conversation with a team member can run through the scenario three times before the actual conversation takes place. She experiments with different ways of opening the conversation. She observes the difference between a closed question and an open question. She experiences how a direct way of phrasing things comes across differently from a more complex one. And most importantly: after each attempt, she receives detailed, behaviour-focused feedback on how she handled it. Not: “you did well”, but specifically which moments were effective and which weren’t, and why.

For L&D professionals, this adds another dimension: measurability. PractAIce generates data on specific behavioural indicators for each practice session. Was the feedback specific enough? Was there sufficient room for response? How was defensiveness handled? That data, collected across multiple practice sessions, shows for the first time how a team’s feedback skills are developing. And not based on self-reporting, but on observed and factual behaviour.

This also changes the nature of the conversation about feedback culture. No longer based on survey questions where people state that they are ‘open to feedback’, but on observable improvement in how feedback is actually given and received.

Frequently asked questions about giving feedback

What is the difference between feedback and criticism?
The difference lies not in the content, but in the intention and the form. Criticism is aimed at judging the other person; feedback is aimed at enabling improvement. In practice, this means: feedback identifies specific behaviour, describes its effect, and leaves room for a response. Criticism often does only the first, or the second without the first.

How do you give feedback to a colleague who is senior to you? Giving feedback to someone above you requires care in how you phrase it, not compromising on the content. What works in practice: first ask explicitly if there is room for your observation, describe specifically what you have noticed, and leave the interpretation to the other person. “I noticed that I didn’t have the chance to finish my point in this morning’s meeting; I just wanted to mention it to see if that rings a bell” comes across differently from a judgemental statement.

How often should you give feedback?
Research consistently points to frequency over intensity. Short, frequent feedback closer to the moment works better than feedback saved up for a formal meeting. For most working relationships, daily to weekly is a good frequency. Not as a ritual, but as a natural expression of engagement with the other person’s work.

Can you practise giving feedback using AI?
Yes, and in many ways it’s more effective than traditional training. AI role-plays offer the repetition, safety and immediate feedback that deliberate practice requires. What AI cannot replace is the human nuance of an experienced coach or mentor. What AI does enable is for employees to practise the basic skills of giving feedback repeatedly before applying them in real conversations. And this is something that has never before been possible at scale in most organisations.

In conclusion

Giving feedback is a skill whose importance is recognised across the entire working world, yet one in which virtually no one is systematically trained. This is not due to any ill intent; it is a consequence of the fact that, until recently, we had no scalable way of allowing people to practise properly.

AI role-playing has closed that gap. It becomes possible to develop feedback skills in the way science has long prescribed: repeatedly, in realistic situations, with immediate feedback on one’s own actions. For organisations wishing to build a feedback culture, this is a shift that makes all the difference.

Are you unsure how this would work in your organisation? A 15-minute demo of PractAIce shows how a feedback session with an AI avatar unfolds and what data it generates.