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How Artificial Intelligence Shapes Who We Become

How Artificial Intelligence Shapes Who We Become

by Meike Hinnenberg | May 19, 2026 | Impuls series, Leadership and AI, Leadership in the digital transformation | 0 comments

How Artificial Intelligence Shapes Who We Become

Meike’s Reflections on Artificial Intelligence

Do you prefer to listen to this article? Click below to access our AI-generated audio version!

How Artificial Intelligence Shapes Who We Become

Meike’s Reflections on Artificial Intelligence

This is the forth part of MDI’s leadership architect Meike Hinnenberg’s new blog reflection series on AI. You can find the previous parts on our blog site! Stay tuned for more 🙂

How Artificial Intelligence Shapes Who We Become | Lines of Subjectivation

Maybe the most certain of all philosophical problems is the problem of the present time and of what we are in this very moment. (Michel Foucault: The Subject and Power) The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are undistinguishable from it. (Marc Weiser: The computer for the 21st Century)

The Hidden Labor Behind AI – A Berlin Exhibition

May 2026 in Berlin; spring has arrived. Light enters the room, and a quiet warmth settles in the apartment. The window is slightly open. I sit at the same table. Again, coffee – dark, dense, almost earthy in its intensity – fills the room.

While I follow its taste, while I continue working on this text, fragments of the exhibition The Language of Soil, which I visited earlier today, return. In this installation, the artist Anna Ehrenstein directs attention to platform workers in Nairobi, Congo, and Egypt – workers who sustain what is called Artificial Intelligence, and for whom Jeff Bezos once used the phrase “artificial artificial intelligence.”

Employed by outsourcing partners of Big Tech companies, their work remains largely unseen. The exhibition brings together interviews, workshops, and collective narrative formats in a 220° video installation, rendering perceptible the “interplay of (post-)colonial continuities, global economies, and the labor that underpins algorithmic systems“.

Voices from the Invisible Infrastructure

I am watching. I am listening. A father, closely connected to his family, now estranged from his daughter; her presence recalls the CSAM he is required to review and label each day. A woman working as a content moderator, checking and filtering visual material from an armed conflict that has also affected her own family, from whom she has had no sign of life. Syrian refugees, shaped by war, displacement, and flight, now labeling sequences of images – war, torture, suicide, rape, child abuse – images that do not remain external, but return.

Micro-Tasks, Micro-Pay

Payment is calculated per micro-task. Ten, twenty, twenty-five cents. Sometimes less. It accumulates slowly, often to less than two dollars per hour. Contracts remain short. They are extended or they are not. Refusal is possible, but not without consequence. Continuity depends on compliance. The work moves; the workers remain replaceable.

Where Do I Stand in This Formation?

As I follow this movement of memories, questions begin to insist: Where am I located in the formation I am trying to describe? How am I affected by it? How do I relate to it?

Has something like an exterior position been gained through thinking the dispositif of Artificial Intelligence, through its lines of visibility and enunciation? Is this now a stable place from which I can speak with a certain autonomy, perhaps even judge it? Or is this, too, only a movement within the same singular and historically situated configuration?

The Illusion of the Exterior Subject

It would be tempting to assume that what has come into view simply persists as knowledge at my disposal, while I myself remain unaffected. Such a perspective preserves the familiar figure of an exterior, self-assured subject and a stable reality upon which it acts by means of technology. And yet this assumption falters. If Artificial Intelligence is approached not merely as a set of tools but as a condition of world-disclosure, the situation becomes more complex.

If the preceding analysis marks a shift in the conditions of seeing and saying, if what appeared self-evident is shown to depend on structured exclusions, then this shift cannot be limited to the object. It implicates the position of the one who sees and speaks, and with it the conditions under which others remain unseen and unheard. What comes into view does not simply add itself to knowledge; it alters the field in which both subject and world take shape.

Foucault and the Making of Subjects

The man described […], whom we are invited to free, is already in himself the effect of a subjection much more profound than himself.

Michel Foucault’s understood his own work as an attempt “to create a history of the different modes by which, in our culture, human beings are made subjects.” (Michel Foucault: Subject and Power) We are not subjects prior to these processes. We are born into historically specific arrangements, dispositifs, within which we speak and are spoken about, see and are seen, act and are acted upon. Even if this idea is an affront to one’s ego, subjectivity does not precede these relations; it takes shape within them. Or, in a Deleuzian inflection: we are continually in processes of becoming-subject.

Lines of Visibility: Who Gets to Appear

If lines of visibility are conditions of perception – if they determine what can appear, in what form, and from which position – then they do not merely organize objects. They also distribute subjects: they situate them, relate them to one another, and define the positions from which something like a “self” can emerge within a given regime of visibility.

Lines of Enunciation: Who Gets to Speak

If lines of enunciation are conditions of sayability – if they determine who or what can speak, where agency is grammatically and conceptually placed, what can be said and in what form it becomes meaningful – then they also affect the subject. For those who speak are not exterior to these conditions.

They take shape within them. What can be articulated, and from which position it can appear as intelligible, does not simply structure discourse; it structures the one who speaks. Subjectivity emerges here not as origin, but as effect: as something formed within a field of available statements, distinctions, and attributions of agency.

To speak is therefore not only to express oneself, but to enter a space already organized in advance, to adopt positions, to repeat or displace existing formulations, to inhabit or refuse a grammar that distributes agency and responsibility. What appears as a self speaking is inseparable from the conditions of enunciation through which it becomes legible, both to others and to itself.

Lines of Enunciation: Who Gets to Speak

Lines of Subjectivation in the Dispositif of Artificial Intelligence

In a Deleuzian sense, lines of subjectivation do not designate identities or inner states. They are trajectories through which subjects are produced: ways in which beings are called into relation with themselves, assigned positions of responsibility, and made capable or incapable of acting, speaking or refusing. They are neither purely imposed nor freely chosen, but emerge in the interplay of practices, norms, and material arrangements.

Within the dispositif of Artificial Intelligence, such lines are not peripheral; they are constitutive of its operation. They do not merely run alongside technical systems but traverse them, linking infrastructures of computation with everyday forms of self-relation.

We are simultaneously involved in their production and their effects: by generating data, labeling and rating outputs, prompting and correcting systems, but also by adopting Artificial Intelligence as interface, infrastructure and environment. At the same time, we are produced through these same relations and practices – as users, data subjects, workers, experts, and objects of prediction.

The Figure of the User

One dominant line of subjectivation produces the figure of the user. Here, the subject is addressed as an interacting point within a system, defined through traces of behavior and patterns of response. Agency is not denied but redirected: it appears as choice within pre-structured environments, as optimization within given parameters. The subject becomes legible insofar as it is continuously translated into data, and governable insofar as it can be rendered comparable, measurable and adjustable.

The Subject as Data

A further line produces the subject as data itself. In this configuration, life is not primarily addressed as expression but as extractable material. Actions, preferences, and linguistic traces are transformed into features, categories, and probabilities. Subjectivity no longer precedes this process; it is retroactively assembled through classification. What one is becomes inseparable from what one can be made to count as.

The Invisible Worker

Another line concerns labor. Here, subjects appear as infrastructural operators of AI systems: annotators, moderators, raters, validators. Their work is essential yet structurally displaced from visibility. It appears only in functional form, as “human-in-the-loop,” as quality control, as correction, while the conditions of its production remain largely unacknowledged. Subjectivation takes the form of simultaneous centrality and erasure.

The Subject of Expertise

A further line produces subjects of expertise. Engineers, researchers, and ethicists are positioned as rational stewards of complex systems. Responsibility is localized at the level of technical decision-making, while broader political and economic structures recede into the background. In this way, agency is reorganized as competence, and critique is often translated into questions of design, optimization, or governance.

The Predictive Subject

Finally, a predictive line of subjectivation renders individuals as anticipatable entities. In domains such as policing, border regimes, or welfare systems, subjects appear as risks, scores, or probabilities. They are addressed not primarily in relation to what they do, but in relation to what they are expected to do. In this configuration, subjectivation operates in advance of action: it produces subjects through the pre-structuring of possible futures.

Alternative Practices: What the Dispositif Cannot Fully Capture

However, not all lines of subjectivation find equal conditions of existence within the dispositif of Artificial Intelligence. Alongside those described above that are actively produced and stabilized, there are others that remain structurally disfavored, forms of becoming-subject that do not easily enter regimes of datafication, optimization, or classification. These are not external to the field, but they appear as weak intensities within it, continually at risk of being neutralized or translated into more legible forms.

If lines of subjectivation traverse the dispositif in this way – if they produce us even as we reproduce them – then the question cannot be limited to which subjects are made possible, but must also address which remain difficult to sustain, and how this difference is lived. If they emerge in the interplay of practices, norms, and material arrangements, a further question arises: what other forms of becoming-subject might be opened through different practices? And which forms of self-relation do we, in turn, sustain or reinforce?

Alternative Practices: What the Dispositif Cannot Fully Capture<br />

Writing: From Struggle with Meaning to Selection Among Outputs

What is the difference between writing a text in the slow proximity of one’s own words – hesitating, revising, following a thought that resists formulation – and producing a text through a system that calculates probable continuations? What shifts in the relation to language, if expression no longer emerges from a struggle with meaning, but from selection among pre-structured possibilities? What kind of subject takes shape when writing becomes prompting, when articulation becomes navigation within a space of outputs already statistically composed?

What becomes of thought when it is no longer allowed to remain without immediate result? What changes if attention is not held in suspension – wandering, returning, lingering – but is continuously operationalized as input, as signal, as resource? What kind of self is formed when thinking is oriented towards an immediate answer, rather than toward the possibility of not yet knowing what it is that one thinks?

What happens to relation when conversation is displaced by mediation? When the effort to encounter another – through hesitation, misunderstanding, goodwill, care, kindness – is replaced by a system that purportedly anticipates, summarizes, or simulates response? What is lost when affect appears as something that can be retrieved on demand, rather than something that emerges in the unpredictability of presence?

What becomes perceptible when an artwork interrupts the smooth passage from image to category? When what is seen does not immediately resolve into recognition, but remains suspended – irreducible to function, resistant to immediate use? What kind of subject emerges in such a moment, in which perception is not yet captured by classification, and meaning does not stabilize into a single trajectory?

And what shifts when the figure of the “annotator” ceases to appear as function and becomes encounter? When the one who labels, filters, and corrects is no longer integrated as an invisible component of the system, but appears as a situated other, whose experience cannot be exhausted by the categories that depend on it and who makes a claim on us? What becomes unstable when this presence can no longer be fully translated into data, role, or task?

Points of Non-Coincidence: Where Other Trajectories Begin

These questions do not lead outside the dispositif. They do not restore an untouched subject prior to its formation. But they begin to indicate points at which its operations do not fully close, and thus sites at which what Waldenfels calls Antwortlichkeit becomes possible. For in each case, something remains that does not coincide with its capture: a hesitation in language, a surplus in perception, a resistance in relation, a remainder in the other that exceeds the roles through which they are made intelligible.

It is perhaps here – not beyond, but within these moments of non-coincidence – that other trajectories of subjectivation become thinkable. Not as stable alternatives, but as fragile deviations: ways of speaking, seeing, and relating that do not entirely align with the imperatives of calculation, prediction, and optimization, and that, precisely in this misalignment, keep the field from becoming fully closed and protect us from totalization.

Which Forms of Life Do We Sustain?

What these movements begin to make visible is a relation that resists simplification. We are not external to the dispositif we describe. We do not stand before it as sovereign subjects, capable of steering it from a position of independence. We are formed within it – through its lines of visibility, its regimes of enunciation, its processes of subjectivation. What we can see, what we can say, what we can become is never simply our own.

And yet, this does not exhaust the relation. For if we are shaped within these configurations, we are not only their effect. We participate in their continuation. We stabilize them through our practices, our repetitions, our forms of use. But precisely in this, a different possibility emerges: that what is reproduced can also be shifted. That even within the field that forms us, there are movements – hesitations, deviations, reconfigurations – through which other trajectories of subjectivation can be fostered.

Neither Determined Nor Free: A More Demanding Question

The question, then, is not whether we are determined or free. It is more demanding: which forms of life do we sustain through the ways we see, speak, and relate? Which subjects do we become when we align ourselves seamlessly with these systems – when we allow their operations to pass through us without resistance, when we accept their abstractions as sufficient descriptions of ourselves and others? And what becomes unavailable in this alignment: which forms of attention, of relation, of language, of responsibility begin to recede when they are no longer practiced?

Conversely, what might it mean to remain within these formations without fully coinciding with them? To inhabit their structures, but not to let them settle entirely into what we take ourselves to be? If there is no outside from which to act, then intervention must take place within the very relations that bind us – within the practices through which subjectivity is continuously produced and reproduced.

Toward the Distribution of Forces

It is here that another dimension comes into view. For the dispositif does not only organize what can be seen, said, and become; it also distributes forces. It channels, intensifies, and stabilizes them. It produces asymmetries, accumulations, and thresholds. To understand how these movements hold, how they persist, and how they might be altered, it becomes necessary to follow not only lines of visibility, enunciation, and subjectivation, but also the lines along which forces are arranged, transmitted, and transformed.

Meike Hinnenberg

Meike Hinnenberg

Learning & Development Architect

Meike Hinnenberg is a trainer and Learning and Development Architect at MDI Management Development GmbH and specializes in communication, conflict management, diversity & inclusion, and lateral leadership.

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by Zeca Ruiz | Dec 3, 2025 | Impuls series, International leadership development, Leadership in the digital transformation | 0 comments

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Do you want to listen to this article? Click here to access our AI generated audio version!

 

Generation Z isn’t the Problem, but Our System is

The discomfort we feel in relation to them reveals that something in us needs to change, because when an entire generation steps away from the same path, perhaps it is not the generation that is lost, but the path itself that is poorly designed.

Zeca is our MDI Trainer based in Latin America and an expert on generational cooperation. This blog article is the first part of a series – read below to find out what he thinks about the youngest generation in the workforce, Generation Z, and let’s start a discussion on LinkedIn!

Today, in leadership conversations, it has almost become a mantra to say that “young people from Generation Z are lost and we cannot expect much from them.”

As a corporate trainer I repeatedly hear complaints or questions that express how difficult it has been for us to relate to this generation.

GenZ – The Useless Generation?

Many leaders describe this generation as immature, fragile, hard to manage, not very committed, rebellious or even disrespectful. And this narrative has become so common that it starts to sound like an absolute truth.

We have reached a point where some companies have simply stopped hiring apprentices from this generation. They have turned their attention to professionals over fifty who, even at the end of their careers, still fit the current ways of working.

As the good contrarian I like to be, I want to bring up a point that only a minority takes the time to investigate.

Reflect, don’t judge!

Reflect, don’t judge!

When we evaluate a behavior only through the lens of the discomfort it causes us, we completely lose the ability to understand its function and existential role.

In the paradigm of complexity, we understand that subjectivity is an inseparable part of the system, including the observer, and that every behavior carries an internal logic that only reveals itself when we examine the context that produces it, not just the effect it generates in us.

It is like judging a book only by its cover. What we feel when we look at the cover, without knowing the real content, says much more about us than about the book.

In the same way, when we look at Gen Z, we do not see only who they are and what they do, we also see the contrast between the Generation Z way of existing and the way we were formed, our beliefs, our world models and the scale we learned to use to measure behavior, ours and others.

And if both the environment has shaped Gen Z and has also shaped the way we judge them, then we need to change the lens of this observation and step away from unilateral judgment.

We need to start asking ourselves, why are they like this, what are these behaviors responding to, which structures taught this generation to act the way it does and what role these responses are playing in today’s society.

Putting Gen Z Into Context

If we look at this Gen Z phenomenon from a systemic perspective, and not a reactive one, it becomes clear that no generation collectively “wakes up” more fragile, more rebellious or more difficult simply by choice.

Every behavior is always a reflection of the environment, always a condition inherent to the context, an adaptive response to specific conditions that are present.

And for me, based on the topics I explore and study, the behavioral expression of Generation Z is not pointing to their weakness, as we like to assume. It is pointing to the deep obsolescence of the system around them.

Every generation is an adaptive response to the environment it inherits from the previous one and Gen Z is no exception. They are a response to a world that has changed faster than organizations have been capable of following.

And let me be clear about something.

I am not here to idealize Gen Z or place them on any pedestal, I also see they carry traits that challenge them deeply, regardless of the system they inhabit.

They can be anxious, impatient, prematurely exhausted, emotionally overwhelmed, and often unprepared to sustain prolonged discomfort. These are real characteristics that demand development, maturity and guidance.

But acknowledging their difficulties does not contradict what I am saying, it actually reinforces it. Because the turning point comes when we stop looking only at what they lack and start recognizing how much of our own worldview, our expectations and our outdated structures shape the very behaviors we criticize.

The moment we take responsibility for the lens through which we see them, we finally create the conditions for growth on both sides.

Putting Gen Z Into Context

Why is Gen Z like this? (before labeling, we must contextualize and understand)

Before making any judgment, it is worth looking at this generation with analytical sobriety and recognizing the quality of their most striking traits, such as their authenticity, their search for meaning, their intolerance for incoherence, their rejection of rigid hierarchies, their heightened emotional sensitivity, their digital fluency and their constant questioning.

Born into the digital age, members of Generation Z arrive in the workplace with very clear expectations for agility, transparency and innovation.

And because they often bring an entrepreneurial and autonomy driven mindset, they tend to challenge traditional paradigms and seek more horizontal structures, with authentic and coherent leadership.

Seeing the Bigger Picture

These elements are not isolated characteristics, they are expressions of a way of existing that was shaped by an environment radically different from the one that structured the ways of the previous generations.

And although these traits are sometimes interpreted as opposition to earlier generations, or as the result of having had too many comforts which would have weakened their capacity for effort and discipline, they are actually a very interesting starting point for deeper, contextual investigation.

After all, as always happens in the transition between generations, these ways of behaving are adaptive responses to conditions that simply did not exist before.

So the invitation here is to broaden our perspective and look beyond isolated behavior. It is to observe the scenario that shaped this generation, the environment and the conditions that gave rise to each trait and to each way that Gen Z responds to the world.

Conclusion

Gen Z isn’t a sign of decline—they’re a sign that our systems haven’t kept pace. Their behavior points to the gaps in how we lead, organize and define work. When we stop labeling and start listening, we see that their traits aren’t flaws but responses to a world that changed faster than our structures did.

The real question isn’t what’s wrong with Gen Z, but what their reactions reveal about the environment we built. Once we shift the lens, it becomes clear: Generation Z isn’t the problem. They’re the diagnosis. The work ahead lies with us.

Zeca Ruiz

Zeca Ruiz

Leadership Trainer and Consultant

Zeca Ruiz is a Leadership Trainer, Facilitator and Consultant in Human and Organizational Development. He works in leadership development across Latin America and Europe, with experience in cultural transformation processes, team dynamics and the integration of systemic methodologies into corporate practice. He is a specialist in complex thinking, a generative coach and an integrative therapist, working at the intersection between human behavior, learning and the evolution of systems. He leads trainings, talks and development programs that combine depth, clarity and practical application to prepare people and organizations for high complexity environments.

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by Jana Wölfl | Aug 28, 2025 | Impuls series, Leadership in the digital transformation, Training Insights | 0 comments

How to Stay Connected: Leadership in Challenging Times

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Staying connected: Leadership in challenging times

In our new video podcast format, “Voices of Leadership – an MDI Spotlight Series,” we regularly bring leadership experts in front of the camera to talk to them about their passions in leadership development.

Our first guest was Peter Grabuschnig – we spoke with him about the challenges in the current work climate, received his tips for new leaders, and discussed a topic close to his heart. Read this blog post to learn more about our first podcast episode!

What really matters to Peter

Right at the beginning, Peter introduces us to the topic close to his heart – connectedness in challenging times.

“I’ve noticed that we are more connected than ever before, but people feel little real connection.”

He explains that, especially with the changes brought about by the COVID-19 pandemic and new home office regulations, it has become more difficult to connect with one another, both among employees and between leaders and employees. At the same time, we are increasingly losing touch with ourselves and our values.

Peter emphasizes that it is an important challenge to restore this sense and be passionate about something again. He also says that he likes to use personality models in his training sessions. These can help participants to meet each other halfway and create a pleasant working environment despite personality differences.

Peter’s best feedback

When it comes to training, we ask Peter what feedback he remembers most. He tells us about participants who were skeptical at first but ended up giving him a high five with total enthusiasm.

He also says that participants often tell him that they’re using the tools they learned and that it’s working.

“I don’t think there’s anything better than that.”

What really matters to Peter

What should leaders change?

Remove judgment and listen consciously. Peter asserts that (negative) judgment, especially in conversations with employees, only causes lasting harm and demotivates employees.

At the same time, he says it is essential for leaders to listen consciously to their employees and thereby build a genuine relationship. The main thing here is to give the other person your full attention and show genuine interest.

“Genuine connection doesn’t take long. A few short sentences are enough.”

He also emphasizes that different people in a team are important assets and that sufficient communication is the most important tool here.

What will challenge us in the coming years?

For Peter, one thing is clear: we need human contact to actively combat increasing loneliness.

“Humans are social beings. We are community creatures; we need other people. Oxytocin is released when we hug someone, not when we have a nice MS Teams meeting with someone.”

Working from home means that many interactions with colleagues are lost. We are often more productive at home, but at what cost? Peter sees this as the biggest challenge – how can we balance productivity and connectedness in a hybrid, rapidly changing world?

Peter as a time traveler

Finally, we asked Peter what advice he would give his younger self if he could travel back in time. His answer: He doesn’t have to know everything. As a young trainer, he often felt that he had to be able to do everything and design the perfect training program. Now he knows:

“Being present is much more important than perfection.”

Authenticity also plays a major role: “If I am authentic, then hopefully my participants can be too!”

Conclusion

Our conversation with Peter showed us how important genuine connection is in today’s work environment. Leadership does not mean always knowing everything, but rather being present, listening, and consciously shaping relationships. Especially in times of remote work and hybrid structures, creating closeness and trust remains a central task.

Peter reminds us that leadership does not primarily work through processes or tools, but through people. Authenticity and genuine interest are often the key to strengthening teams in the long term.

Want to listen to the whole podcast? Here you can access the YouTube video! Follow us to make sure you don’t miss any more conversations with leadership experts.

Jana Wölfl

Jana Wölfl

Marketing Assistant

Jana Wölfl is a marketing assistant at MDI and works on our blog. She has already been responsible for several areas of marketing, such as designing our new website and administering our personalist.at portal.

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AI Hears; Humans Listen: Become a Master of Attunement

Prefer to listen to the article? Click below to access our AI speech-generated audio. However, if you want to read it as usual, keep scrolling.

AI Hears; Humans Listen: Become a Master of Attunement

Not Black Mirror. Not Severance. The reality we’re in is starting to feel a lot more like Her.

According to eye-opening research published in Harvard Business Review, the most common use of generative AI isn’t writing code, synthesizing data, or even creating content.

It’s companionship.

Let that sink in. At the frontier of one of the most advanced technological revolutions in history, people aren’t just looking for answers or performance enhancements—they’re looking to feel heard.

The Burnout I Didn’t Catch

At this year’s Leadership Horizon, my partner Bailey Parnell and I are set to announce the groundbreaking AI product we’re building at SkillsCamp. It’s the fastest-moving venture I’ve ever been a part of. 

In my previous companies, we’d maybe pivot once or twice a year. Now we’re pivoting multiple times a day. Strategies shift at breakfast. Features change by lunch. Priorities rearrange by dinner.

It’s exhilarating. It’s also exhausting.

In the middle of this whirlwind, we missed something important—one of our teammates was struggling to keep up. The constant change had become disorienting. They were slipping into the early stages of burnout. And here’s the part that really hit me:

I wrote the book on beating burnout.

The Burnout Gamble is explicitly about how leaders can prevent precisely this kind of thing. On top of that, during my keynote speech at Leadership Horizon a few years back, I preached the gospel of human-centered leadership—of slowing down to tune in. Of attunement.

Even though I had been hearing my colleague, the truth is, I hadn’t been listening.

I had only been reacting. Optimizing. Building the future of leadership. But not asking, in the way that only a human can:

“Kaif al hal?” (كيف الحال؟)

It’s Arabic for “How are you?”—but it literally translates to: How is your heart doing? AI can’t ask that. At least not yet. And even when it can, it won’t mean it.

Everything’s Amazing. Nobody’s Happy.

Over the past year, we’ve seen an explosion in AI capabilities. From Claude and DeepSeek to custom GPTs, agents, copilots, and beyond—we’ve unlocked tools that can write like us, talk like us, and think faster than us. And yet amid all this brilliance, morale is shaky. Anxiety is rising. Relationships at work feel more fragile. Loneliness is still trending. 

Somehow, despite everything being amazing…nobody seems to be fully happy. And that’s because the problem isn’t just about what’s being built. It’s about what’s being missed.

Become a Master of Attunement

Stephen Covey once said:

“The biggest communication problem is that we do not listen to understand. We listen to reply.”

These days, we don’t even reply—we prompt. We’ve become so good at asking AI the right questions, we’ve forgotten how to ask each other the real ones.

So here’s an idea: Let AI be your productivity engine. Your logic brain. Your pattern-detecting genius. But let you be the soul. The resonator. The attuner. The etymology of attunement is “to bring into harmony.” It’s not about fixing people—it’s about feeling with them.

Become a Master of Attunement

In leadership, this means mastering what I call the Listening Ladder:

Emotion

Response Style

Example

Pity

Recognize

“That’s awful. At least it’s almost Friday.”

Sympathy

Care

“I’m sorry to hear that. That sounds tough.”

Empathy

Feel

“I hear you—it sounds like this workload is really taking a toll.”

Compassion

Act

“Let’s find a way to ease your load together.”

Attunement isn’t passive. It’s an active presence. It’s emotionally intelligent alignment. It’s not just knowing what someone is going through—it’s standing with them in it, and saying: I’m here.

But Isn’t AI Getting Good at This?

Sure, AI can detect emotional cues through text or tone. It can simulate concern. It can even give decent advice. But there’s a line it can’t cross: It doesn’t feel.

AI won’t sit in silence with a teammate who just got a life-changing diagnosis. It doesn’t notice how someone’s voice slightly trembles when they mumble “I’m fine.” Machines can’t experience shame, grief, awe, or love.

And it can’t ask, from the heart: How is your heart doing?

So yes, AI may one day outpace us in logic, language, and even innovation. But the sacred skill of soul-to-soul listening—that remains deeply, beautifully human.

The Future of Leadership

Ray Kurzweil prophesied that the 21st century won’t bring 100 years of progress—it will bring the equivalent of 20,000.

But no matter how far we go, one truth stays constant: People don’t quit companies. They quit leaders who don’t listen.

As the future of work accelerates, the leaders who thrive won’t be the ones who outpace AI. They’ll be the ones who partner with AI—and lead like humans.

Consider this your invitation to become irreplaceable. Learn to attune. Ask real questions. Listen with your whole body. Respond with presence. And the next time someone on your team seems off, don’t just check their output.

Check their heart.

Hamza Khan

Hamza Khan

Keynote Speaker

Hamza Khan is a best-selling author, award-winning entrepreneur, and globally-renowned keynote speaker whose TEDx talk “Stop Managing, Start Leading” has been viewed over two million times.

The world’s leading organizations trust him to enhance modern leadership, inspire purposeful productivity, nurture lasting resilience, and navigate constant change.

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by Florian Biedermann | Mar 25, 2025 | Leadership and AI, Leadership in the digital transformation, MDI Inside | 0 comments

MDI’s Leadership Lab: Unlocking the Future of Leadership Training

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Click here to access our AI-generated audio version! Have fun listening 😉

MDI’s Leadership Lab: Unlocking the Future of Leadership Training

The world of learning and development (L&D) is evolving with the advancements in artificial intelligence (AI), offering new possibilities alongside established training methods. Traditional formats—classroom sessions, workshops, and coaching—remain essential for leadership development, providing deep insights and impactful learning experiences.

AI complements these approaches by enhancing personalization, enabling real-time feedback, and increasing scalability, making leadership development even more effective and accessible. AI is changing all of that by combining data analysis, machine learning, and natural language processing. Here are some inspiring ways AI is shaping the future of leadership learning and development— developed by MDI’s (Management Development International) AI Leadership Lab.

Roleplays and simulated scenarios: practicing leadership in a safe space

The MDI AI Leadership Lab enables the creation of realistic leadership simulations. These are not static case studies, but dynamic, adaptive scenarios where AI responds to a leader’s decisions in real time.

Imagine a virtual simulation where a leader faces underperformance and team tension with a new employee, a salary negotiation, or a feedback talk with a team member who frequently dominates team discussions. The MDI AI Leadership Lab provides you with a virtual roleplay with a team member that can be played via chat or a voice interface. These roleplays can introduce unexpected twists—like exaggerated demands of an employee or a challenging stakeholder response—to test how the leader adapts under pressure.

These roleplay simulations allow leaders to practice decision-making, conflict resolution, communication skills, and further challenges in a risk-free environment. They build confidence and competence by providing immersive, hands-on learning experiences.

Roleplays and simulated scenarios: practicing leadership in a safe space

Real-Time, AI-Powered Feedback

Leadership development has traditionally relied on periodic evaluations—often at the end of a program or after performance reviews. With the MDI AI Leadership Lab, each leader can receive honest, constructive feedback that is impossible to manipulate at any time.

This AI-powered tool can analyze leaders’ communication styles, decision-making patterns, and even their tone of voice during meetings. Using natural language processing, these tools provide real-time feedback on clarity, emotional tone, and collaboration tendencies. Such as the „Communication for Leaders“-roleplay that encourages you to practice the BID (Behavior, Impact, Development) model to provide constructive feedback that motivates and guides improvement.

Here, a leader might receive instant suggestions to adjust their communication style to foster better team engagement or tips on handling conflict with greater empathy. This immediate feedback allows leaders to course-correct at the moment rather than waiting weeks or months for formal evaluations.

AI as a Virtual Coach: Support on Demand

For decades, MDI has been providing coaching support next to leadership training. However, not every leader has access to a personal mentor or coach. Furthermore, it often takes some time for the coach and coachee to find a suitable time slot to start the coaching. With the MDI AI Leadership, everyone can have a virtual coach in their pocket or on their desktop – at any time. This AI-driven coach provides just-in-time advice, from managing difficult conversations to preparing for performance reviews and many other topics.

These virtual coaches can analyze real-time data, monitor progress, and offer personalized suggestions for improvement. They ask thought-provoking questions, provide empathetic guidance, help to identify patterns, and support you in solution finding.

This 24/7 support ensures leaders get the guidance they need, exactly when they need it. You can communicate with MDI AI virtual coach via voice interface or, if the room situation makes it inappropriate to talk to the coach, you might use its chat interface.

    AI as a Virtual Coach: Support on Demand

    Ask me anything – the MDI AI Leadership Knowledge bots.

    Imagine you have very specific questions about your leadership role, but no one is competent to ask. Wouldn’t it be fantastic to have a knowledge partner who is available anytime you need him?

    This kind of genie in a bottle is the MDI AI Leadership knowledge bot. Organized by topics such as lateral leadership, negotiation skills for executives, conflict management, resilience, self-leadership or inclusive leadership, and many more, these knowledge bots always deliver helpful information when required. These AI Leadership knowledge bots were trained with exclusive training materials dealing with topics that have been successfully trained for years, as well as MDI publications, and thus have extensive knowledge in the respective subject areas.

    A Smarter Way to Learn

    This enhanced capability allows AI agents to deliver more sophisticated and context-aware support, greatly improving the customer experience – in various languages. In times when informal learning and micro-learning are becoming increasingly important, chatbots are extremely attractive learning companions.

    After all, 90% of our learning takes place informally – not in the traditional seminar room – but in an exchange with each other or on the job! But what if you can’t learn in a group or if you don’t have a highly competent colleague at your side, the learning bots are the perfect solution here: rarely out of order for repairs, available to learners around the clock, and a great learning partner when learning and seeking for information.

    Conclusion: AI is a partner in leadership growth

    AI is not a replacement for human leadership, but it is a powerful partner in developing it. When used thoughtfully, AI can make leadership development more personalized, data-driven, and impactful.

    The future belongs to organizations that embrace this partnership—combining cutting-edge technology with timeless human wisdom to develop leaders who are not only competent but compassionate, self-aware, and ready to lead in an ever-changing world.

    So, the question is: Are you ready to harness AI’s potential to grow the next generation of leaders? If so, feel free to test the MDI AI Leadership Lab.

    Florian Biedermann

    Florian Biedermann

    Learning & Development Consultant at MDI

    Florian Biedermann is a Learning & Development Consultant at MDI (Management Development Institute) – a global consulting company that offers solutions for leadership development. His focus is on making complex issues understandable and inspiring people to think – and act. Florian previously worked for many years as an author and manager in the e-learning sector, after spending over a decade as a freelance journalist.

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    by MDI & ARS Academy | Jan 14, 2025 | Best Practice, Leadership in the digital transformation, Leadership Tips | 0 comments

    Challenges and Solutions for Leadership in 2025

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    Leadership challenges and solutions in 2025

    In an increasingly complex and uncertain world, companies and their leaders face numerous challenges. In collaboration with the ARS Academy, we conducted the Management Survey 2024. It offers valuable insights into the key issues that companies are currently dealing with and will deal with in the future.

    It shows how companies can address internal and external challenges, with a particular focus on talent acquisition and work-life balance. Learn more about the results of the management survey in this blog post!

    Key challenges: from talent management to digitalization

    1. recruiting and retaining talent

    For 67% of leaders, attracting and retaining qualified employees is the biggest challenge. The shortage of skilled workers, which is further exacerbated by demographic change, also makes it increasingly difficult to find suitable talent and retain them in the company in the long term.

    Smaller companies with up to 250 employees are facing particular challenges. They often have fewer resources than large companies and must therefore be more creative to be perceived as attractive employers and to compete with the offers of larger companies.

    2. Economic uncertainty

    More than half of the respondents (54%) cite economic uncertainty as a problem that makes their planning more difficult. Volatile markets, geopolitical conflicts and rising operating costs mean that companies need to develop more flexible strategies.

    3. Technological change

    52% of companies see technological change as a key challenge. While digital skills are becoming increasingly urgent, investments in new technologies are prioritized more highly by smaller companies (65%) than by larger companies (41%).

    4. Sustainability and ESG

    Sustainability is also becoming more and more of a priority, mainly due to issues such as climate change and new legal requirements. 43% of companies have incorporated ESG strategies into their day-to-day operations, but only 12% reward the achievement of these goals with management bonuses.

    This shows that sustainability is an issue for many companies, but is not yet fully anchored for all of them.

    Key challenges: from talent management to digitalization<br />

    Work-life balance: aspiration and reality

    Our survey makes it clear that the work-life balance of employees is a top priority for leaders: 93% consider it to be “very important” or “somewhat important”. Interestingly, only 71% of leaders see their own work-life balance as equally fundamental.

    This disparity shows that some leaders need to strengthen their role model function when it comes to self-care in order to promote a sustainable corporate culture in the long term.

    The most important measures for a better work-life balance

    1. Remote work and home office: 85% of companies offer alternative working methods. We see this as a clear sign that adaptable workplace designs are becoming more and more common.
    2. Flexitime models: 82% offer flexible working hours to help their employees achieve a better work-life balance.
    3. Regular appraisals: 81% of leaders also use feedback sessions to identify and adapt to employee needs.
    4. Supporting physical and mental health: In addition to fitness programs (56%), offers such as stress management courses or access to psychological counseling (47%) play a central role. These measures help to promote the long-term well-being of employees.

    The 4-day week as a pilot model

    It is interesting to note that 12% of companies have already introduced a four-day working week – a model that could increase productivity and employee satisfaction in the long term. This change could also serve as a forerunner for further flexible working time models.

    work life balance

    Strategic solutions for the challenges of continuing education and adaptability

    63% of companies rely on training to prepare employees for future challenges. Larger companies in particular (over 250 employees) focus on team-building measures and employee retention programs (66%).

    50% of companies also plan to adapt their strategies to be able to react more flexibly to external influences. In small companies, this figure is as high as 59%, which demonstrates their agility.

    Technological innovations

    In addition to the introduction of digitization strategies (40%), technical training (55%) and access to modern hardware and software (51%) are essential components of the transformation efforts. Nevertheless, only 30% of the companies surveyed have implemented an AI strategy, which indicates a great need for further development in this area.

    Leadership skills 2025: humanity and technology in harmony

    The leaders of tomorrow will need a wide range of skills. According to our survey, the most important skills are:

    • Communication skills (62%): Crucial for leading teams and managing crises.
    • Leadership (59%): Essential for providing clear vision and strategy.
    • Problem-solving (48%): Critical for finding innovative solutions to complex problems.
    • Emotional intelligence (43 %): This is essential for fostering empathy and trust within the team.

    These skills are crucial for overcoming the challenges of an increasingly complex and dynamic working environment and inspiring employees. Leaders must not only be technically competent, but also able to guide their teams through change and uncertainty.

    Conclusion: A new balance between people and technology

    The results of the 2024 management survey show that leaders need to prepare for a world in which both technological innovation and employee needs are important.

    Successful leadership means remaining flexible, promoting talent, and always putting employees first. Striking the right balance between efficient work processes and a sustainable corporate culture will make all the difference – for your company and for your employees.

    MDI Management International

    MDI Management International

    MDI is a global leader in leadership development with 60 years of experience. With offices worldwide and a network of over 250 international consultants and trainers, MDI offers training and consulting services in various languages. The company designs and implements customized programs for leaders at all levels, high potentials, experts, project managers, and salespeople – locally, internationally, and globally.

    ARS Academy

    ARS Academy

    The ARS Academy is Austria’s largest private provider of professional seminars and is represented in all federal states. Around 1,000 selected top experts from business, practice and law pass on their knowledge in around 1,200 different events to around 18,500 participants per year.

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    by Raphaela Pouzar | Aug 27, 2024 | Leadership and AI, Leadership in the digital transformation, Short Knowledge Bits | 0 comments

     

    Navigating the Ethical Challenges of Algorithmic Decision-Making

    You prefer to listen to this article? Click here to access our AI-generated audio version:

    Navigating the Ethical Challenges of Algorithmic Decision-Making

    by KI generated

    https://blog.mdi-training.com/wp-content/uploads/2024/08/Navigating-the-Ethical-Challenges-of-Algorithmic-Decision-Making1.mp3

    Navigating the Ethical Challenges of Algorithmic Decision-Making

    Artificial Intelligence (AI) is transforming our world, from personalized recommendations to advanced medical diagnostics. However, as AI becomes more integrated into our lives, a critical issue has emerged: algorithmic bias. This bias occurs when AI systems are trained on flawed or incomplete data that lacks diversity, leading to unfair or discriminatory outcomes and often perpetuating existing inequalities.

    What is AI Bias?

    AI bias arises when algorithms reflect and amplify societal prejudices embedded in their training data. For example, suppose an AI system is trained predominantly on data from one demographic group. In that case, it may perform poorly for others, leading to unfair decisions in areas like hiring, healthcare, and law enforcement.

    The Dual Nature of AI

    AI offers immense benefits, but these are accompanied by significant risks. In healthcare, for instance, AI can assist in diagnosing diseases, but if the training data lacks diversity, the AI may misdiagnose conditions in underrepresented groups, exacerbating health disparities.

    Global Implications: Data Colonialism

    AI bias isn’t just a local issue—it has global ramifications. In many cases, data from the Global South is used to train AI systems that benefit the Global North, a practice known as data colonialism. This exploitation deepens global inequalities, as those in the Global South often do not share in the benefits of AI technologies.

     

    Global Implications: Data Colonialism

    Addressing AI Bias

    To mitigate AI bias, it is essential to adopt a responsible approach to AI development. This involves recognizing the duality of AI—its potential for both benefit and harm—and taking proactive steps to minimize risks. Here are some key strategies:

    1. Diverse and Representative Data: Ensuring that AI systems are trained on diverse and representative datasets is crucial. This includes data from different demographic groups, geographic regions, and socio-economic backgrounds to minimize bias.
    2. Transparency and Accountability: AI systems should be transparent, with clear explanations of how decisions are made. Additionally, there should be mechanisms for accountability, allowing users to challenge and understand decisions that negatively impact them.
    3. Ethics by Design: Integrating ethical considerations into the design and development of AI systems is vital. This includes ongoing assessments of how AI systems impact different groups and the potential risks involved.
    4. Global Collaboration: Addressing AI bias requires global collaboration, with input from diverse stakeholders, including those from marginalized communities. Policymakers, industry leaders, and civil society must work together to create regulations and standards that ensure AI development is fair and inclusive.

    Conclusion: A Path Forward

    As we move forward into an increasingly AI-driven world, it is crucial to remain vigilant about the biases embedded in these technologies. Only by acknowledging and addressing these issues can companies ensure that AI serves as a tool for positive change, rather than perpetuating existing inequalities.

    Murikah, W., Nthenge, J. K., & Musyoka, F. M. (2024). Bias and ethics of AI systems applied in auditing – A systematic review. Scientific African, 16, e02281. https://doi.org/10.1016/j.sciaf.2024.e02281

    Ukanwa, K. (2024). Algorithmic bias: Social science research integration through the 3-D Dependable AI Framework. Current Opinion in Psychology, 58, 101836. https://doi.org/10.1016/j.copsyc.2024.101836

    Caro-Burnett, J., & Kaneko, S. (2022). Is society ready for AI ethical decision-making? Lessons from a study on autonomous cars. Journal of Behavioral and Experimental Economics, 98, 101881. https://doi.org/10.1016/j.socec.2022.101881

    Arora, A., Barrett, M., Lee, E., Oborn, E., & Prince, K. (2023). Risk and the future of AI: Algorithmic bias, data colonialism, and marginalization. Information and Organization, 33(3), 100478. https://doi.org/10.1016/j.infoandorg.2023.100478

    Raphaela Pouzar

    Raphaela Pouzar

    Marketing Team Assistant

    Raphaela Pouzar, a Bachelor of Business Administration student at IMC Krems, works at MDI as a marketing assistant alongside her studies. Additionally, she is currently pursuing an AI certificate from Harvard Business School.

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    by Gunther Fürstberger | Aug 23, 2024 | Digital Transformation, Leadership in the digital transformation, MDI Inside | 0 comments

    The ARS Seminar: Lateral Leadership and AI Role-Playing

    Immerse yourself in the world of lateral leadership with us and experience realistic role-playing with state-of-the-art AI technology! These methods bring a breath of fresh air to the world of leadership development and show how modern approaches can be successfully applied in practice.

    Role-playing in Training

    Role-plays have been used in communication training for decades to try out real-life challenges in a safe environment and develop skills. These usually take place either with voluntary participants in front of the group or several groups in parallel.

    In the first case, the trainer can give direct feedback, in the second case more participants have the opportunity to practice. Not everyone loves role-playing, but overall it is an effective method for developing social skills.

    However, the method also has disadvantages that can now be overcome by artificial intelligence: Trainers or even professional actresses don’t work for free. Training and application dates may be far apart, and by then much will have been forgotten.

    Role-playing in training

    Large Language Models

    With the help of LLMs (Large Language Models), on the other hand, it is possible to train as often as required at a fraction of the cost shortly before real-life use. The ChatGPT 4.0 app offers well-functioning language input and output and can access extensive knowledge, such as the DISG model or the Harvard Principles of Negotiation.

    Some trainers at MDI have been experimenting with it for a year now, and the participants are enthusiastic. We demonstrate a role play in front of the group, involve several participants, and then pass on the prompt used for self-practice.

    AI in Various Management Systems

    We have further developed the prompts so that the feedback from the AI is precisely aligned with the models taught in the seminar. In addition, the resistance intensity of the AI role-play partner has been optimized.

    Anyone who would like to experience this in reality will have the opportunity to do so in the ARS seminar “Lateral Leadership” from 22.10. to 23.10. Further exciting role-playing functions are currently being developed.

    Mag. Gunther Fürstberger

    Mag. Gunther Fürstberger

    CEO | MDI Management Development International

    Gunther Fürstberger is a management trainer, author and CEO of Metaforum and MDI – a global consulting company providing solutions for leadership development. His main interest is to make the world a better place through excellent leadership. He has worked for clients including ABB, Abbvie, Boehringer Ingelheim, DHL, Hornbach, PWC and Swarovski. His core competence is leadership in digital transformation. He gained his own leadership experience as HR Manager of McDonald’s Central Europe/Central Asia.  At the age of 20 he already started working as a trainer.

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