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Leading in the Age of AI: How AI Discourse Shapes Responsibility and Power

Leading in the Age of AI: How AI Discourse Shapes Responsibility and Power

by Meike Hinnenberg | Mar 18, 2026 | Impuls series, Leadership and AI, Leadership Tips | 0 comments

Leading in the Age of AI: How AI Discourse Shapes Responsibility and Power

Meike’s Reflections on Artificial Intelligence

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

Leading in the Age of AI: How AI Discourse Shapes Responsibility and Power

Meike’s Reflections on Artificial Intelligence

This is the second of seven parts of MDI’s leadership architect Meike Hinnenberg’s new blog reflection series on AI. You can find the first part here! Stay tuned for more 🙂

Chapter II – Lines of Enunciation

By distinguishing Artificial Intelligence as an industrial apparatus from machine learning as a set of practices, Crawford performs a gesture of ethical resistance. She interrupts the smooth circulation of the term, exposing Artificial Intelligence not as a settled object but as a line of enunciation – and in doing so opens a different path through the field.

In Deleuze’s sense, lines of enunciation are neither utterances nor texts, neither speakers nor doctrines. They are conditions of sayability that circulate within a dispositif, delineating what can be named, thought, and acted upon.

Most often, lines of enunciation remain invisible precisely because they work so well. They do not appear as commands, norms, or ideologies; they slip into language as description, into grammar as agency, into names that seem to pre-exist the things they gather. They do not ask to be believed: one does not need to agree with a line of enunciation to use it.

How AI Discourse Shapes Reality and Responsibility

These lines are not primarily repressive; they are productive. They bring objects into being (AI), generate problems (alignment, bias), propose solutions (ethical AI), and sketch futures (AI will transform everything). A critique that treats them merely as false representations, therefore, misses the point. Their force lies not (only) in what they conceal, but also in the realities they help bring into existence.

Understanding this productivity – and, with it, understanding technology not simply as an instrument to be used wisely but as a mode of world-disclosure – is essential, especially with regard to the question of responsibility. We are not outside the dispositif. We are not independent of the social, technological, and linguistic structures through which the world becomes accessible to us. Our relation to ourselves and our access to reality are shaped within them.

How AI Discourse Shapes Reality and Responsibility

Response-ability

What is therefore required is not the illusion of standing beyond these structures, but the effort to understand how the dispositif operates: what realities it brings into being, how we are positioned within it, and how we might relate to it, act within it, or even shift its lines. For now, being independent of these conditions does not mean we would not be responsible. Responsibility may instead take the form that Bernhard Waldenfels calls Antwortlichkeit (response-ability): a responsiveness to what addresses us before we fully understand it, a response that can never entirely catch up with what precedes it.

Let us follow this path a little further to see how it shapes the field. If we turn, for example, to the website of the OECD, we read:

AI holds the potential to address complex challenges from enhancing education and improving health care, to driving scientific innovation and climate action. However, AI systems also pose risks to privacy, safety, security, and human autonomy. Effective governance is essential to ensure AI development and deployment are safe, secure and trustworthy, with policies and regulation that foster innovation and competition.

How Discourse Limits What Can Be Questioned

The OECD text speaks in a language in which Artificial Intelligence already acts: it drives, addresses, and enhances. Politics enters only later, as a moderating hand. In this grammar, Artificial Intelligence appears as an agent capable of benefit or harm, yet never itself fundamentally in question. Within this frame, one may debate safety, trust, and regulation, but more structural questions about extraction, power concentration, or the desirability of AI as such struggle to surface as relevant statements. The force of such enunciation lies not in persuading belief, but in pre-structuring the field of speech itself.

By distinguishing Artificial Intelligence as an industrial apparatus from machine learning as a set of practices, Crawford renders such a line of enunciation visible and thereby intervenes in the field of sayability. By questioning whether Artificial Intelligence is even artificial or intelligent, she shows that what appeared as an autonomous historical actor is in fact a constructed convergence: an industrial apparatus, a planetary infrastructure grounded in colonial continuities and distributed human labor.

What material and historical infrastructures make AI possible?

By shifting the question from “Is AI fair?” to “What material and historical infrastructures make AI possible?”, the unity of the term Artificial Intelligence fractures like the ice layer of a winter-frozen lake.

And another layer of the acoustic landscape begins to surface: the breathing of ventilation shafts, the murmur of moving earth, the metallic heartbeat of drills, the slow chewing of stone by machines, the deep-throated hum of engines, the churning of propellers folding the sea behind them, the wind threading through stacked containers, a quiet choreography of clicks and pauses labeling one image after another, bodies trying to keep time with logistics, repetition measured in beeps, the percussion of parcels in transit – a subdued sonority of work that must remain unnoticed, a human rhythm beneath the supposedly smooth surface of automation.

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.

  • LinkedIn

Join us on May 5th for our yearly Leadership Horizon Conference!

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AI Ethics for Leaders: Why Context and Critical Thinking Matter More Than Ever

by Meike Hinnenberg | Mar 11, 2026 | Impuls series, Leadership and AI, Learning Transfer | 0 comments

AI Ethics for Leaders: Why Context and Critical Thinking Matter More Than Ever.

Meike’s Reflections on Artificial Intelligence

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

AI Ethics for Leaders: Why Context and Critical Thinking Matter More Than Ever

Meike’s Reflections on Artificial Intelligence

This is the first part of a new AI blog series by our Senior Learning Architect, Meike Hinnenberg. Read her thoughts below and stay tuned for more parts to come!

The history of mining, like the devastation it leaves in its wake, is commonly overlooked in the strategic amnesia that accompanies stories of technological progress. […] As San Francisco drew enormous wealth from the mines, it was easy for the populace to forget where it all came from […] Just like the mines that served San Francisco in the nineteenth century, extraction for the technology sector is done by keeping real costs out of sight.

(Kate Crawford: Atlas of AI)

[…] – that is, as I said, the use of active forgetfulness, a porter at the door, so to speak, a custodian of psychic order, quiet, etiquette. From that we can see at once how, if forgetfulness were not present, there could be no happiness, no cheerfulness, no hoping, no pride, no present.

(Friedrich Nietzsche: The Genealogy of Morals)

It is immediately by deviating from equilibrium of animals, from tranquility – a departure engendered by the fault of Epimetheus – that mortals occur. Before the deviation, there is nothing. Then the accidental event happens, the fault of Epimetheus: to have forgotten humans. Humans are the forgotten ones. Humans only occur through their being forgotten; they only appear in disappearing.

(Bernard Stiegler: Technics and Time, 1)

Introduction

It is the beginning of February 2026 in Berlin; shortly after the big blackout in southern Berlin; shortly after several deaths and devastating losses in southern Europe in the wake of Storm Harry; shortly after a judge of the International Criminal Court was sanctioned by the United States; shortly after a cold wave driven by a destabilized jet stream claimed lives in the U.S.; shortly after deadly storms and floods across South and Southeast Asia left thousands displaced, hundreds dead and entire regions submerged; shortly after Russian strikes left thousands of households in Kyiv without heating while, almost in the same breath, the Ukrainian government entrusted the development of the namesake lithium deposit in the Kirovohrad region to TechMet – an Irish company partly backed by the U.S. government’s Development Finance Corporation and the U.S. financial firm Rock Holdings – drawing the country into the competitive circuitry of the global battery economy; shortly after …

It is the beginning of February 2026 in Berlin, and the air outside is sharp with cold. Inside my aging apartment, warmth gathers despite the leaky windows. The radiators whisper with gas that has traveled from Norway, the Netherlands, Belgium, the United States, or Azerbaijan, holding back the easterly winds for now. I sit in my kitchen. Milk warms slowly on the stove; coffee – probably carried from Africa, Asia, or South America – rises in the espresso pot and fills the room with its wonderful, familiar scent.

I open my computer, assembled through supply chains that fade into opacity, dependent on minerals, infrastructures, and forms of labor that rarely enter the frame. I open it to read the news and to begin research for a series on AI I am planning to write – aware, somewhere in the background, that even a question posed to a machine draws on energies and resources far beyond the gesture of typing it.

From this kitchen table, my orientation turns toward two recent points of departure: Kate Crawford’s Atlas of AI and her video essay  Mapping Empires.

Meike’s Reflections on Artificial Intelligence

Chapter I – The Dispositif of Artificial Intelligence

In Atlas of AI, Kate Crawford peels back the layers – conceptual and material alike – that have accrued around what we have come to call Artificial Intelligence, revealing a construct whose hidden assumptions we inhabit daily, largely unaware of the consequences they set in motion.

Her analysis unfolds as a kind of cartography, recalling Gilles Deleuze’s notion of the dispositif: a field traced by lines of visibility and invisibility, by grand narratives and what they render mute, by modes of subjectivation, fractures, continuities, and crossings – lines that intersect and mutate without ever solidifying into a universal structure.

Technologies of Domination

To draw nearer to this dispositif, to traverse its terrain, Crawford adopts the figure of the atlas. The atlas makes palpable the material and spatial dimensions condensed under the name Artificial Intelligence, even as these very conditions – its infrastructures, labors, and extractive foundations – are frequently displaced from view. 

At the same time, it affirms the situatedness of all knowledge: each map offers only a partial orientation, shaped by choices of scale, emphasis, and omission. In this convergence of aesthetic visual ordering and epistemic claim, Crawford shows that mapping is not a neutral description but a creative and political act.

Even as Crawford insists on the partiality of her own account – presenting her work as an invitation to follow emerging paths, to linger in zones of disparity, and to witness how particular perspectives come into being – she remains attentive to the darker history of the atlas itself. For atlases have never been innocent instruments of orientation alone; they have also served as technologies of domination.

The God’s Eye View

It is precisely this ambivalence that grounds her central hypothesis: that under the name Artificial Intelligence, such cartographic power is once again being mobilized. Along familiar routes of colonial exploitation and driven by an ambition no longer to draw an atlas of the world but to stand in for it, this impulse recentralizes power within the field of AI, advancing claims of universality and totality that rest on extractive regimes.

In doing so, it seeks to translate movement, communication, and labor into data, rendering the world legible from what Crawford describes as a supposedly objective, centralized “God’s eye view”.

Deterritorialization and Reterritorialization

The atlas itself operates through a double movement of what Deleuze would call deterritorialization and reterritorialization. While its cartographic abstractions unsettle fixed spatial relations and open new pathways of thought, they also carry a long-standing capacity for capture and domination.

Crawford’s intervention can be read as an attempt to amplify the deterritorializing potential of the atlas, even as she meticulously traces the reterritorializing operations to which colonialism and contemporary AIrepeatedly return.

The Ethical Task

Dispositifs, as singular and historically situated configurations, neither begin from nor arrive at the universal. And yet, in their operation, they repeatedly give rise to gestures of universalization and ambitions of totality, effects that emerge from within rather than from any transcendent ground. It is for this reason that such claims need to be traced genealogically, followed back along the paths through which they come to assert themselves.

Against this horizon, the ethical task is not to oppose totalization with a quasi-moralistic counter-universal, but to remain attentive to these movements as they unfold: to introduce shifts, frictions, and alternative pathways that keep the field open.

Ethical resistance, if it is to remain worthy of the name, must itself resist the temptation of ideology, universalization, and closure. For wherever resistance hardens into morally indignant certainty or ideological form, it risks reproducing – under the guise of critique – the very logics of universalization and reterritorialization it set out to unsettle.

Meike Hinnenberg

Meike Hinnenberg

Learning & Development Consultant

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

  • LinkedIn

Join us on May 5th for our yearly Leadership Horizon Conference!

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A Success Story – When AI Sharpens Human Judgement

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by Claude MacDonald, Rafael Ungvari | Mar 6, 2026 | Customer Story, Digital Transformation, Leadership and AI | 0 comments

A Success Story – When AI Sharpens Human Judgement

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

When AI Amplifies Human Judgment: A Customer Success Story

About This Project

At MDI, we believe that great leadership and sales development isn’t just about knowledge transfer — it’s about behavior change. This customer story reflects a collaboration between Claude MacDonald, MDI trainer and Sales Culture Architect, and Rafael Ungvari, MDI’s AI Product & Solution Lead, who designed and implemented the AI-driven learning environment for this engagement. Together, they bring a rare combination: deep human expertise in consultative selling and the technical capability to turn that expertise into scalable AI-powered practice tools.

The Challenge: Great Training, Not Enough Practice

Our client is a global B2B organization in the industrial chemicals industry, operating across multiple business units with complex sales cycles and technically sophisticated offerings. Sales leaders and managers play a critical role in developing the consultative selling capability of their teams, which makes closing the practice gap not just a training question but a leadership priority.

The goal was clear: strengthen Discovery skills. That means helping sales professionals ask better questions, genuinely uncover client needs, qualify opportunities more accurately, and walk into customer conversations fully prepared.

Here’s the honest challenge: the existing training worked. It created shared language and awareness. But awareness alone doesn’t change behavior. And behavior only changes with practice — lots of it.

Think of elite athletes. They don’t improve by playing more games. They improve because the practice-to-play ratio is deliberately high. In sales, that ratio is almost always inverted. Real customer conversations are high-stakes environments — there’s limited room to experiment, fail, and try again.

That’s exactly the gap we needed to close.

Why AI – and Why Role Play?

The answer wasn’t more classroom time. It was deliberate, repeatable practice at scale.

AI-driven role play made it possible to create realistic Discovery conversations on demand. Participants could practice, reflect, adjust, and replay scenarios multiple times — something impossible to replicate with peer simulations or occasional classroom role plays.

Without AI, the solution would have looked like traditional role play: useful, but hard to scale, difficult to repeat, and dependent on the availability of skilled practice partners. With AI, we could give every participant a realistic, challenging practice environment they could return to again and again.

Crucially: AI didn’t replace human judgment. It amplified it by giving people more chances to sharpen their questioning, their listening, and their situational awareness before the stakes were real.

How the Solution Was Designed

The concept was straightforward: AI avatars simulated customer interactions specifically designed to challenge participants on the exact capabilities that matter most in Discovery — questioning quality, listening and sense-making, problem framing, and opportunity qualification.

A typical session combined a short conceptual input with an AI-driven discovery role play, followed by structured reflection and a facilitator-led debrief. Participants encountered realistic customer responses and had to adapt their approach in real time — not follow a script.

The human-AI balance was intentional. Human facilitators anchored the learning in business reality, coached participants on consultative behaviors, and helped translate practice into field application. AI provided the environment: repeatable, realistic, and safe to experiment in.

The Challenge: Great Training, Not Enough Practice

What Participants Experienced

The most significant shift was in the practice-to-play ratio. Participants could run the same scenario multiple times, testing different questions and conversational strategies. This dramatically increased the practice-to-play ratio, accelerating skill development in Discovery conversations. The experience felt realistic, engaging, and directly connected to daily work — not abstract, not theoretical.

A few voices from participants (anonymized):

“The AI role plays were incredibly helpful. Being able to repeat scenarios helped me improve my discovery conversations.”

“This was a breath of fresh air — challenging, practical, and directly applicable.”

“The AI tools made it easier to structure my thinking before real customer calls.”

Results: What Actually Changed

Observed outcomes included stronger Discovery conversations with better questions and sharper listening, more structured pre-call preparation, improved opportunity qualification, and increased confidence in leading customer discussions.

Compared to traditional formats, the AI-enabled approach proved more scalable (accessible to more participants, more often), more effective (higher practice volume, faster skill development), and more sustainable (embedded as an ongoing practice tool rather than a one-time event).

Key Takeaway: AI Works Best When It Amplifies Humans

The most important lesson from this project is deceptively simple: AI is most powerful when used to amplify human judgment, not replace it.

Building consultative selling capability — especially in Discovery — requires far more deliberate practice than traditional training formats can realistically provide. AI-driven role play creates a scalable, repeatable way to embed that practice into sales development programs.

When does this approach make sense? When the capability gap is behavioral rather than knowledge-based, when practice volume matters, and when you need a safe environment for experimentation and failure.

When doesn’t it make sense? When the learning goal is primarily about mindset shifts, relationship dynamics, or complex emotional intelligence work — areas where human nuance and real relationship context are irreplaceable.

The future of effective sales training isn’t AI or humans. It’s knowing exactly where each one adds the most value — and designing for both.

Interested in exploring AI-driven role play for your sales or leadership development programs? Contact us at https://mdi-training.com/ai-enhanced-leadership-training/

Are you interested and you want to hear more from Claude MacDonald? Claude will speak at our next Leadership Horizon conference on May 5th with his keynote Business Case: When AI Amplifies Human Judgment: Lessons from the Field. 

Get your tickets now!

Claude MacDonald

Claude MacDonald

Sales Culture Architect & Leadership Strategist

Claude MacDonald is recognized as an expert in sales culture transformation. Over the past 25 years, Claude has trained and coached more than 25,000 managers, professionals, and employees from prominent organizations in Canada, the United States, and Europe. His work focuses on building the mindsets, skills, and habits that drive lasting commercial performance — from frontline sales professionals to senior leadership teams.

  • LinkedIn
Rafael Ungvari

Rafael Ungvari

AI Product & Solution Lead

Rafael is AI Product & Solution Lead at MDI and is working to redefine leadership development through artificial intelligence. To implement this idea, he has worked with our team to establish the MDI AI Leadership Lab, which serves as a hub for experimenting with and applying AI solutions together with clients and trainers.

His work builds on his studies in business informatics at WU Vienna, where he combines business perspectives with technical expertise to develop practical and sustainable digital solutions.

  • LinkedIn

Save your tickets and join us on May 5th!

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How You Deal With Neurodiversity as a Leader

How You Deal With Neurodiversity as a Leader

by Iris Kandlbauer | Feb 3, 2026 | Leadership Impact, Leadership Tips, Short Knowledge Bits | 0 comments

How You Deal With Neurodiversity as a Leader

You prefer listening to this article? You can find our AI-generated audio version below!

How You Deal With Neurodiversity as a Leader

What might be behind “strange” behavior in a team—and how leaders can deal with it constructively.

Irritating behavior—people who are absent

Everyone knows them: the colleague who never attends team events, prefers to work with headphones on, and hardly ever consults with others, but who works with incredible precision and delivers great results. Or the colleague who is chaotic, often late, full of ideas that have made many a project a success, but lacks structure.

It’s easy to jump to conclusions: unmotivated, uncooperative, lazy, they just need to make a little effort… Discussions are held, behavior is demanded – and often nothing happens. Or worse, performance declines and sick days increase. What is going on?

What could really be behind it

Instead of jumping to the conclusion that someone “just doesn’t want to,” it’s worth taking a look behind the façade. Because conspicuous or supposedly inappropriate behavior often has deeper causes:

  • Trauma & developmental experiences: People who have experienced trauma in the past often withdraw in social contexts.
  • Social anxiety/anxiety disorders: What looks like disinterest can be deep insecurity or fear of embarrassment.
  • Cultural or linguistic differences: Misunderstandings can easily arise when norms and communication styles don’t match.
  • Mental illness: Depression or overload often manifest themselves insidiously, for example through social isolation or frequent mistakes.
  • Chronic exhaustion: Care work, illness, or constant pressure lead to cognitive and emotional exhaustion.
  • Personality traits & temperament: Not everyone is extroverted or team-oriented—and they don’t have to be.
  • Neurodiversity: Autism, ADHD, giftedness, or dyslexia affect approximately 20% of people. Often, these conditions are accompanied by special strengths—but also by behavior that deviates from the “norm.”
Neurodiversity at Work

The other perspective: Challenges as strengths

What may appear to be a deficiency at first glance can actually be a resource:

  • Viktor Frankl developed logotherapy from his trauma.
  • Frida Kahlo turned emotional pain into art that still moves people today.
  • People with ADHD bring creative ideas to teams.
  • Introverts like Warren Buffett make wise decisions with caution.

Those who embrace diversity also get a diversity of solutions, ideas, and perspectives.

What does this mean for leadership?

Good leadership recognizes that people tick differently—and that this is precisely where great potential lies. It’s not about making everyone the same, but about creating the right conditions so that individual strengths can become visible and effective.

In practice, this means:

  • Instead of rushing to judgment: Look closely, observe, and understand patterns
  • Don’t just lay down rules: Have conversations, listen, and ask about needs
  • Instead of one-size-fits-all solutions: Allow for flexibility and individual ways of working
  • Don’t fixate on shortcomings: Focus on existing strengths and opportunities for development

This does not mean simply accepting problematic behavior. But it does mean understanding its origin before reacting—and then providing targeted and appropriate guidance.

Ideas for your leadership practice:

See irritations as an invitation to dialogue.

Ask yourself: What does this person need to be able to work well? What conditions promote performance and belonging for this person?

Because the ability to lead diversity determines how future-proof a company really is.

Iris Kandlbauer

Iris Kandlbauer

Trainer and Coach

Iris Kandlbauer is a coach and trainer for leadership development with a focus on dealing with diversity in teams. She supports managers in understanding and productively utilizing different ways of thinking, working, and communicating—for example, through giftedness, neurodiversity, or cultural influences. She previously worked for many years as a teacher, trainer, and specialist in interpersonal dynamics, and now brings her educational experience to bear in effective leadership coaching and sustainable team development.

  • LinkedIn

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by Anita Berger | Dec 17, 2025 | Leadership Tips, Learning Transfer, Short Knowledge Bits | 0 comments

Why It Matters When Transformation Gets Hard

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Self-Efficacy: Why It Matters When Transformation Gets Hard

Change can be exhausting.
Especially when things are unclear, priorities shift, and not everything is well-designed or well communicated.

You adjust. You adapt. You cope.
Sometimes with commitment, sometimes with resistance, sometimes with quiet frustration.

In moments like these, one factor becomes especially relevant:
how self-effective you experience yourself within the change — how oriented, capable and able to act you feel.

Not because the process is perfect.
But precisely because it often isn’t.

Change is a Process — Not a Straight Line

Change and transformation don’t happen in neat sequences.
They move in a recurring cycle of:

  • Making sense — understanding what is changing and why
  • Focusing & aligning — deciding where to place attention and energy
  • Acting & experimenting — trying things out, adjusting in motion
  • Reflecting & integrating — making meaning of what happened and what it changed

At the same time, how effective each phase becomes depends largely on how people experience themselves within it.

Change is a process — not a straight line

A Self-Reflection Checklist to Strengthen Self-Efficacy in Change

If you are currently involved in or affected by a change or transformation process, these questions are an invitation to pause and explore your own experience.

1. Perception — How am I making sense of what is happening?

  • What am I noticing most in this change right now?
  • What interpretations am I forming, and what alternative perspectives might exist?

2. Focus — Where is my attention in relation to influence and concern?

  • What am I currently concerned about that lies outside my control?
  • Where do I see opportunities to act or influence within my own Circle of Influence?

3. Mindset — How am I relating to learning and uncertainty?

  • What thoughts or reactions emerge when outcomes are unclear or mistakes happen?
  • How might a growth-oriented perspective change the way I approach this situation?

4. Personal change preference — What do I need to stay effective?

  • What kind of change energises me, and what kind of change drains me?
  • What conditions would help me stay engaged and capable in this phase?

Self-efficacy doesn’t mean controlling the change or having all the answers.
It means staying connected to your own agency within the process — even when the path isn’t clear.

Change processes need structure, direction, and people who design and guide them.
They also rely on individuals who can navigate their own perceptions, focus, and mindset within that structure.

Both sides are equally relevant.

  • Which of these questions resonates most with you right now?
  • Where do you notice your self-efficacy strengthening — or slipping — in change?

I’m looking forward to hearing your perspective!

Anita Berger

Anita Berger

MDI partner and trainer

Anita Berger is an executive coach, consultant, and trainer with a strong focus on leadership development in the VUCA/BANI world, design and facilitation of transformation processes and organizational culture development, as well as international human resources management. She is a co-owner and partner of MDI, Management Development International. With over 25 years of experience in management and leadership positions (including in the management of Coca-Cola Hellenic Austria & Slovenia & Konica Minolta Business Solutions) in various industries and company sizes, from medium-sized businesses to international corporations. Numerous contributions focus on leading virtual and hybrid teams, agile change management, organizational and leadership culture, as well as strategic talent management.
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