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How to Build a Psychological Safety Net at Work

How to Build a Psychological Safety Net at Work

by Florian Biedermann | Aug 28, 2025 | Best Practice, Leadership Tips, Short Knowledge Bits | 0 comments

How to Build a Psychological Safety Net at Work

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How to Build a Psychological Safety Net at Work

Some of you might recognize these situations at work: You have an idea but hold back—because you’re not sure how it will be received. Or you want to ask a question but stay quiet—for fear of embarrassing yourself.

What’s often behind this? A lack of psychological safety. It keeps people in protective mode instead of creative mode. Our L&D consultant, Florian Biedermann, explores psychological safety in his newest blog article. Find out what he’s thinking and how he approaches this topic below!

Google already uncovered this in 2012 through its Project Aristotle:

In high-performing teams, everyone has a voice. Everyone is treated with respect. The way leaders and team members interact matters deeply. That’s why it is essential for leaders to create a space where people feel:

“I can say what I think—without fear of negative consequences.”

This simple sentence is the heart of a concept gaining global traction: psychological safety—a work environment where people feel free to ask questions, admit mistakes, voice ideas or concerns… without blame or shame.

But here’s the real question:
Can it actually be trained?

Why leaders play a key role

Leaders are climate shapers. Their mindset and communication style strongly influence whether openness can thrive. But in reality? Many leaders operate under high pressure—and often react defensively to mistakes or conflicting opinions. So it’s no surprise that psychological safety has become a core focus in modern leadership development.

Why leaders play a key role

Can it be trained?

Yes.
But not through theory. Only through experience, reflection, feedback, self-awareness, and real behavioral training.

Here are a few practical approaches:

Feedback exercises in safe settings
→ How do I react when someone challenges me?

Rehearsing error-friendly conversations
→ How do I show that learning matters more than blame?

Coaching on language and mindset
→ How do I speak when I truly want to listen?

Integrating external perceptions
→ How do my people actually see me?

Since live sparring partners aren’t always available, we at MDI developed a tool to help:

Our AI Leadership Lab allows you to simulate conversations—on topics like communication, conflict management, or negotiation—via text, voice, or even with an avatar.
You get personalized feedback to identify your blind spots and grow your strengths.

Confidence is not a nice-to-have

Psychological safety is not a fluffy soft skill—it’s a critical business factor and a strategic management tool.

You can’t demand it.
But you can build it—through practice, reflection, and leaders who are willing to grow.

Over to you

Is psychological safety already part of your leadership training? What helps you create a safe climate—and where do you hit your limits?

Share your ideas with Florian on LinkedIn!

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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AI Hears; Humans Listen: Become a Master of Attunement

AI Hears; Humans Listen: Become a Master of Attunement

by Hamza Khan | Apr 18, 2025 | Digital Transformation, Leadership and AI, Leadership in the digital transformation | 0 comments

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 Marcin Swierkocki | Apr 10, 2025 | eLearning, Learning Transfer, Short Knowledge Bits | 0 comments

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

Aligning Training Goals with Organizational Business Objectives

In my experience, aligning training with business objectives is one of the biggest challenges – it requires in-depth preparation for a training project, e.g. understanding the cultural aspects of the organization, the potential obstacles that stand in the way of implementing newly acquired skills, and acquiescence on the management to implement new habits.

Here are several proven strategies that I’ve found effective in enhancing knowledge transfer and ensuring that training delivers real business impact:

1. Encourage Practical Application During Training

Enabling practical application while running a course – Whenever possible, I integrate real-life, job-relevant exercises into the training sessions. This allows employees to practically apply new skills in a safe environment classroom. By working with scenarios that reflect their day-to-day challenges, they are better equipped to transfer those skills back to the workplace.

2. Create a Safe and Supportive Learning Environment

A safe and supportive environment – this means e.g. helping delegates translate theory into practice. Additionally, the trainer’s role is to promote a culture of continuous collaboration while managing a seminar. I encourage the sharing of knowledge and good practices immediately among the delegates.

Create a Safe and Supportive Learning Environment

3. Continuously Evaluate and Improve Training Effectiveness

Monitoring and improvement through regular evaluations. I monitor the effectiveness of knowledge transfer by feedback interviews during and after training sessions. This allows me to focus on continuous improvement of the training content and tailor future sessions more effectively based on real needs. This iterative process of refinement is crucial for maintaining relevance and maximizing the return on training investment.

4. Reinforce Learning Through Follow-Up Sessions

Sustainable learning doesn’t end when the training session concludes. We, at MDI Training, hold regular 2-hour follow-up sessions usually 4 to 6 weeks after the training to ensure continued development and to address any emerging challenges. These sessions help reinforce key messages, revisit challenging topics, and provide a platform for participants to share their implementation experiences. They are also an opportunity to clarify lingering questions and re-energize commitment to behavioral change.

Conclusion

Using the above strategies can significantly increase the effectiveness of skills knowledge transfer in an organization.

For more information, feel free to address me directly – marcin.swierkocki@mdi-training.com or send me a DM on Linkedin. I’d also love to hear your tips and experiences that support your training effectiveness.

Marcin Swierkocki

Marcin Swierkocki

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Marcin Swierkocki works as an HR business consultant who has specialized in L&D, change- and project management. He brings over 25 years of international experience in change management and operational development with him. His personal motto is influenced by Viktor Frankl: ‘Between stimulus and response there is a space. In that space is our power to choose our response. In our response lies our growth…’. His personal inspiration comes from his optimistic and positive character and by draining the energy that successfully supporting others gives him.

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Efficiency with AI in Leadership Development

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Efficiency with AI in Leadership Development

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Efficiency with AI in Leadership Development

Perhaps the first AI hype is already over, but it paves the way for a more realistic view. AI transformation is progressing at different speeds in different industries.

However, the training industry is among the pioneers: machine learning has enormous potential to make human learning more efficient, effective, and cost-effective. Since 2023, we have been experimenting intensively with artificial intelligence as a provider of leadership development and are happy to share our experiences.

AI in everyday business: a fixed routine in meetings

For a year and a half, AI has had a permanent place in every company management meeting. At least one current topic is supplemented by an LLM (Large Language Model) with a perspective or recommendation.

This practice has proven itself and enables more informed decisions with minimal time investment. Experiments with automatic logging, on the other hand, have proven less successful.

In August 2023, we launched AICO (Artificial Intelligence Co-Trainer), which has since been supporting us with energy exercises, music selection, transfer tasks, and as a knowledge source for participant questions in the seminar. Shortly after that, we tested the first ChatGPT role-playing game in a seminar and were impressed by the positive participant feedback. Initially, we provided the prompts as a transfer task.

AI transformation roadmap: planning at the company level

In January 2024, we launched a company-wide AI transformation roadmap. This means that we plan how AI can be used in key areas of the company every quarter to ensure that the entire organization is involved in this development.

In our OKR (Objectives and Key Results) planning meeting for the second quarter, we determined that no offer would be sent to customers without an AI component that covers at least 10% of the learning journey. Customers will still have the option to book the AI components that were previously free of charge.

AI transformation roadmap: planning at the company level

AI Lab: A role-playing center for real-world scenarios

In the third quarter, we plan to set up an AI lab on our website where all applications can be tested and used in a bundled form. This lab includes a role-playing center for various leadership communication situations. Participants take on the role of the leader, while the AI takes on the role of the employees.

A keyboard is no longer necessary – the role play is done by speaking and listening. After completion, the leaders receive targeted feedback that refers to the learned communication models. The role play can be repeated as often as desired, not only in the seminar but also when the situation arises in real life.

The future of learning: from 2D avatars to “superpowers”

Just as e-learning has replaced knowledge transfer in training over the last 20 years, AI has the potential to revolutionize skills development today. Currently, role-playing on the phone is still purely auditory, but soon visual avatars will be integrated as role-playing partners.

AI applications with 3D avatars for virtual reality glasses already exist. However, we suspect that 2D avatars will initially be used as learning partners because they are easier to use. These avatars are already supported by so-called “superpowers”. For example, Hume.ai gives AI coaches empathy and enables feedback on the current emotional state of the role-playing participant using voice analysis.

Real avatars as knowledge messengers and the next step in learning transfer

We are experimenting with “real avatars” of trainers who are available to participants as knowledge messengers after the seminar. This new type of learning transfer support enables agile learning when needed. Despite all efforts, learning transfer has often been a neglected topic in the industry.

Our leadership agent project (“LAgent”) is proving more challenging: we are developing an AI agent that can proactively pursue short-and long-term goals together with the leader. However, the LLMs currently available are still limited in their memory function, which would be necessary for responsible co-leadership. But this is precisely where development is progressing rapidly, and it is becoming increasingly easier to develop AI agents.

Conclusion: AI transformation in learning and development

Overall, the AI transformation in the area of learning and development is a fascinating field and is contributing significantly to the development of organizations and, by extension, society.

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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Weak vs. Strong AI: Unraveling the Myths

Weak vs. Strong AI: Unraveling the Myths

by Raphaela Pouzar | Jul 22, 2024 | eLearning, Leadership and AI, Short Knowledge Bits | 0 comments

 

Weak vs Strong AI – Unraveling the Myths

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Weak vs Strong AI – Unraveling the Myths

Artificial Intelligence has become an integral part of our daily lives, from virtual assistants like Siri and Alexa to recommendation systems on Netflix and Amazon. However, there remains a significant misconception that AI can do more than humans, including possessing human-like understanding and reasoning abilities. To clarify these misconceptions, it’s essential to distinguish between “weak AI” and “strong AI,” the two paradigms within AI research.

Weak AI vs. Strong AI

Weak AI, also known as narrow AI, is designed to perform specific tasks such as image classification, game playing, or speech recognition. These systems excel at their designated functions but cannot understand or infer the underlying causes behind the data they process.

They operate based on pre-defined rules and large datasets, showcasing behavioristic characteristics rather than true cognitive processes. For example, deep learning, a subset of weak AI, uses artificial neural networks to identify patterns and make predictions but does not possess true understanding or consciousness.

In contrast, strong AI, or artificial general intelligence (AGI), aims to replicate human cognitive abilities. This includes reasoning, understanding, and the ability to learn from experiences like humans. Strong AI is not just a tool for problem-solving but is envisioned to have actual mental states, consciousness, and the capacity for imagination.

Despite its theoretical appeal, strong AI remains an elusive goal, as current AI systems lack common sense and the ability to comprehend hidden processes behind the data they analyze.

Misconceptions about AI Capabilities

One major misconception is that AI can surpass human capabilities in all aspects. While AI systems can outperform humans in specific tasks, such as playing chess or Go, they do not possess the holistic understanding and cognitive flexibility inherent to human intelligence. Current AI, intense learning models, are adept at processing vast amounts of data to make predictions but do so without understanding the context or causality behind the data.

Moreover, the myth that AI is “all algorithms” oversimplifies its complexity. AI systems rely not only on algorithms but also on high-quality data, effective user interfaces, and interdisciplinary research. Reducing AI to just a set of algorithms ignores the broader context of its development and application.

 

Weak vs strong AI-2

The Practical Implications of Weak AI

Despite the limitations of weak AI, its practical applications are profound. Weak AI systems provide scalable, efficient solutions for handling big data and have become ubiquitous in various industries. From spam filters and recommendation systems to voice assistants and navigation tools, weak AI enhances our daily lives by automating and optimizing routine tasks.

The Elusive Goal of Strong AI

Strong AI, with its promise of human-like cognition and understanding, remains a topic of extensive research and debate. Some argue that to achieve strong AI, future research should focus on developing compositional generative predictive models (CGPMs) that mimic the human brain’s ability to infer and understand the causes behind sensory inputs.

However, the realization of strong AI poses ethical and practical challenges, including the risk of manipulation and the need for these systems to align with long-term, homeostasis-oriented purposes. However, the development of strong AI is still a distant goal.

Conclusion

Understanding the distinction between weak AI and strong AI helps dispel common myths about AI capabilities. While weak AI systems provide valuable tools for specific tasks, strong AI remains a theoretical concept, far from realization.

Acknowledging these differences is crucial for setting realistic expectations and guiding future AI research and development. As AI technology continues to evolve, it is imperative to focus on ethical considerations and ensure that these advancements serve to enhance human potential rather than overshadow it.

Butz, M. V. (2021). Towards Strong AI. Künstl Intell, 35(1), 91–101. https://doi.org/10.1007/s13218-021-00705-x

Flowers, J. C. (2021). Strong and weak AI: Deweyan considerations. Künstl Intell. Retrieved from Worcester State University. jflowers@worcester.edu

Liu, B. (2021). “Weak AI” is likely to never become “Strong AI”, so what is its greatest value for us? arXiv preprint arXiv:2103.15294. https://doi.org/10.48550/arXiv.2103.15294

Nussbaum, F. G. (2023). A comprehensive review of AI myths and misconceptions. Review: AI Myths and Misconceptions (Version: October 31, 2023). Retrieved from frank@fgnussbaum.com

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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