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Efficiency with AI in Leadership Development

Efficiency with AI in Leadership Development

by Gunther Fürstberger | Oct 31, 2024 | Best Practice, Leadership and AI, MDI Inside | 0 comments

Efficiency with AI in Leadership Development

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

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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From Lab to Practice: What We Learned With AI

by Rafael Ungvari | 3. September 2025 | Digital Transformation, Leadership and AI, Short Knowledge Bits | 0 Comments

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by Jana Wölfl | 28. August 2025 | Impuls series, Leadership in the digital transformation, Training Insights | 0 Comments

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by Florian Biedermann | 28. August 2025 | Best Practice, Leadership Tips, Short Knowledge Bits | 0 Comments

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by Florian Biedermann | 28. August 2025 | Leadership and AI, learning effectiveness, Short Knowledge Bits | 0 Comments

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The Lasting Impact of Leadership Horizon – Meike’s Perspectives

by Meike Hinnenberg | 2. July 2025 | Leadership Impact, MDI Inside, Short Knowledge Bits | 0 Comments

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AI in Leadership in 2025: Impressions from Leadership Horizon

by Christoph Wirl | 1. July 2025 | Leadership and AI, MDI Inside, Short Knowledge Bits | 0 Comments

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Leadership and AI: Between Responsibility and Opportunity

by Marina Begic | 6. May 2025 | Digital Transformation, Leadership and AI, Leadership Tips | 0 Comments

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AI Hears; Humans Listen: Become a Master of Attunement

by Hamza Khan | 18. April 2025 | Digital Transformation, Leadership and AI, Leadership in the digital transformation | 0 Comments

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Success Through Change: How to Stay Oriented During Transitions

by Anita Berger | 14. April 2025 | Impuls series, Leadership Impact, Leadership Tips | 0 Comments

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by Marcin Swierkocki | 10. April 2025 | eLearning, Learning Transfer, Short Knowledge Bits | 0 Comments

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Step by Step to Success with AI-Powered Solutions

Step by Step to Success with AI-Powered Solutions

by Marina Begic | Oct 31, 2024 | Best Practice, Digital Transformation, Leadership and AI | 0 comments

Step by Step to Success with AI-supported Solutions

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Step by Step to Success with AI-supported Solutions

A successful AI transformation in human resources development does not happen overnight. It is a process that requires a strategic approach and an agile implementation. How do you get employees on board? Combining both poles.

Sound familiar? Employees and colleagues approach you and tell you about the latest AI apps they are trying out. Many of them mention, some do not, that they do not even know whether they are allowed to use AI tools in the company. Your company may be working on a policy right now. There may not yet be a company-wide regulation or it may not yet be known. Don’t worry, you’re not alone in this attitude; 80% of companies are also waiting.

The importance of AI integration for employee motivation and competitive advantage

This could be fatal, on the one hand, because the initial motivation of employees, which is so often desired from the point of view of personnel development and leadership, could be curbed as a result. On the other hand, it could put them at a competitive disadvantage. A possible first-mover advantage shrinks with every day that passes without working on optimization using AI.

In addition to the motivation, some have no interest in the topic of AI and think they can “sit it out” or are unable to exert any influence anyway. So how can we get everyone on board? After all, as we know, we move faster when we’re all rowing in the same direction.

AI Readiness Check: assess the starting position.

Before companies embark on the AI transformation of their HR development, it makes sense to assess their current AI readiness. An AI readiness check helps to evaluate the initial situation and discuss it together. This AI readiness check provides, for example, results in the categories of strategic orientation, know-how, culture, resources, and data after a 10-minute self-assessment.

With a common starting point, it is easier to identify opportunities for integrating AI into the L&D strategy. Such a readiness check can be used in any area of the company.

AI Transformation (1000 x 600 mm)

Agile approach – AI Autonomy Day

Organize an AI Autonomy Day: Provide everyone with a day a year to work on any topic in the field of AI. Provide as little guidance as possible. Also, provide a small budget for any licenses. It is important to note that, by the GDPR, no personal or company data should be transferred to unprotected LLMs.

Trying it out can happen individually, in a team, across departments/hierarchies/teams. Provide a communication platform and make it transparent which topics are being worked on. Set a date for presenting the results. Invite relevant stakeholders and decide together what will be done with the results. Repeat the process every six months or even every quarter.

To take it to a strategic level, we recommend setting up an AI transformation roadmap. This roadmap will track the progress and plans for each area. You can decide whether to share the roadmap with everyone individually or by team/area. The results and the maturity level of the project should be recorded by the company management.

This tool offers you the following advantages:

  • Clear vision and strategic direction
  • Improved communication and alignment with stakeholders
  • Controlled resource and time management
  • Risk reduction and adaptability
  • Focused innovation and development of use cases
  • Structured approach – a clear process gets the ball rolling

To find out what leverage AI can have in your company, you need to have a basic knowledge of AI and the (technical) possibilities of AI (weak AI vs reactive AI vs AI with limited storage capacity) . On the other hand, you need to know your processes very well. Those who already have a detailed process map have a clear advantage here.

As a first step, evaluate the AI potential based on your processes and divide your processes into three process types. Then evaluate the savings potential of the activity to determine your starting point with the greatest potential.



Weak AI vs. Reactive AI vs. AI With Limited Storage Capacity

Weak AI: performs tasks, does not learn new skills (voice assistants, generative AI: image generation, text generation, research & diagnosis)

Reactive AI: does not build up memory, reacts to stimuli (spam filters, recommendation systems based on historical data such as Netflix, Amazon)

AI with limited storage capacity: stores knowledge, learns from it and makes forecasts (weather, finance, self-driving cars, chatbots)

(Source: https://ki-campus.org/videos/ki-in-unserem-alltag?locale=de)

Further training & communication

To use the topic of AI profitably and responsibly for everyone in personal development, in the team, and the company, you cannot avoid acquiring a basic knowledge of AI yourself and motivating others to do the same.

Join communities, exchange ideas with peers, and take small steps. But take them consistently and lead by example. Support your colleagues and managers with training, workshops, exchanges, and networking opportunities. Create personalized wikis and AI assistants (e.g. using GPT Builder) to make knowledge more accessible.

 

Marina Begic

Marina Begic

Head of Business Development – Digital Transformation Driver

Marina has been working on new, effective learning methods and the future of corporate learning for over 15 years. In her current role, she is responsible for Digital Business Development at MDI, where her focus is not driven by the current buzzwords, but primarily on the feasibility of digital transformation for clients such as Erste Group, Lenzing, Semperit, Deutsche Bahn, Andritz AG, Uniqa, Mayr-Melnhof, Frequentis, RHIM. Her greatest strength is bringing loose ends together, which she impressively demonstrates time and time again with her big picture view and multi-dimensional approach. Her greatest passion is to provide learners not only with an experience, but also with real, lasting value for their real challenges.

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Navigating the Ethical Challenges of Algorithmic Decision-Making

Navigating the Ethical Challenges of Algorithmic Decision-Making

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

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Navigating the Ethical Challenges of Algorithmic Decision-Making

by KI generated

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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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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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Leadership in Transition: Insights from Leadership Horizon 2024

Leadership in Transition: Insights from Leadership Horizon 2024

by Christoph Wirl | Jul 4, 2024 | Leadership and AI, Leadership Tips, MDI Inside | 0 comments

Photo credits: Jenny Theolin

 

Leadership in Transition: Insights from Leadership Horizon 2024

This was our Leadership Horizon Conference of 2024! Click here and immerse yourself in the Highlights.

Leadership in transition: Insights from Leadership Horizon 2024

Here you can find the original report by magazine training editor Christoph Wirl: 

A guide to the most effective strategies for integrating artificial intelligence – We report on the Leadership Horizon conference.

MDI’s Leadership Horizon Conference retook place this year on June 4 at SO/Vienna and was dedicated to the increasing fusion of leadership practices and Artificial Intelligence (AI). It served as a platform for the exchange of practical findings and strategies for integrating AI into management processes.

Around 160 HR experts and managers from various industries came together to share their experiences and visions. The event was English-language and hybrid, allowing international participants to attend both online and in person.

The impressive line-up of speakers was consistently compelling. The event offered a successful mix of inspiring keynotes, practice-oriented workshops, and insightful business cases.

The two sides of the AI coin

CEO Gunther Fürstberger opened the conference with a virtual avatar, created with the HeyGen program’s help, and looked very similar to the real speaker. He spoke about the importance of artificial intelligence for both companies and managers.

He showed both sides of the coin: For example, many people have already been killed through the use of AI-controlled drones in war zones. At the same time, however, the use of artificial intelligence in medicine has already saved the lives of millions of people or significantly improved their health.

AI therefore has a clear impact on our society, which is why we need to develop and use this technology responsibly. We need to harness the potential of AI for the benefit of humanity while carefully weighing up the potential risks and ethical challenges.

Photocredits: Jenny Theolin

AI is not magic

When the conference moderators asked the audience who was not yet sufficiently familiar with the topic of artificial intelligence, more than half of the attendees responded. This just goes to show that we need to engage more with this forward-looking topic.

Afterward, magician Tobias Grünfelder from the Abracademy fascinated the participants and drew parallels between the art of magic and artificial intelligence:

“AI is not magic – we just need to look behind the scenes. Just as professional magicians do not rely on a single trick, we should also take a holistic approach to the application of artificial intelligence. It is not enough to see AI as some kind of magic bullet that solves all problems by itself. Instead, it is important to understand the underlying mechanisms and functioning of AI systems to be able to use them effectively and responsibly.”

AI-powered leadership

Johannes von Mikulicz-Radecki also emphasized the complexity of using AI in leadership in his presentation “AI-Powered Leadership”:

“The time when you could experiment with AI and try out different use cases is over. Now it’s about putting what you’ve learned into practice.”

This requires managers to clearly understand the possibilities and limitations of artificial intelligence and the ability to strategically integrate this technology into their business processes. In addition, von Mikulicz-Radecki emphasized the general relevance of AI tools in companies:

“Artificial intelligence is too important to be left only to management.”

Photocredits: Jenny Theolin

An insight into UNIQA’s AI strategies

Later, keynote speaker Cristina Anculescu showed how UNIQA has optimized the employee experience with the help of AI tools. She reported that 47% of Gen Z employees surveyed said they received better career advice from AI than from their managers. For example, some upload their LinkedIn profile to ChatGPT and ask for suggestions for improvement.

In response, UNIQA has used AI to develop and promote individual career paths for its employees. Intelligent algorithms are used to create individual development plans. These are based on the strengths, interests, and goals of individual employees.

The downside of flexible home office arrangements

After the lunch break, renowned expert and speaker Ryan Jenkins was connected live from the USA. The technical implementation went smoothly so that both the participants on-site and the online participants were able to follow his presentation without any problems. He addressed the importance of interpersonal connections within a company:

“When employees feel isolated, they are up to seven times more likely to work inefficiently.”

He noted that due to excessive use of our smartphones and online media, we are often unable to build and maintain relationships with our colleagues. In this day and age, people are more independent of each other than ever before, making it harder to make and maintain connections. Jenkins therefore warned that the often overly flexible home office regulations should be critically scrutinized.

Photo credits: Jenny Theolin

Dangers and fears around AI

Rebecca Johnson presented the possibility of learning using AI avatars and introduced a specific tool that enables particularly effective practice of negotiation skills.

In her final presentation, Bailey Parnell tried to allay the audience’s fears of artificial intelligence. She explained basic concepts such as machine learning and deep learning and introduced various AI tools, including Canva, Suno, Copilot, and image generation software.

She also addressed the potential dangers of AI and discussed possible job losses due to automation, the loss of privacy and the problem of bias in AI systems.

Conclusion on Leadership in Transition: Insights from Leadership Horizon 2024

The Leadership Horizon Conference 2024 once again proved to be a great event for executives who want to integrate AI into their corporate strategies. It provided valuable insights into current trends and inspired thinking about the future role of technology in leadership.

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by Rahpaela Pouzar | Jun 12, 2024 | Leadership and AI, MDI Inside, Short Knowledge Bits | 0 comments

Photo credits: Jenny Theolin

 

From Typewriters to AI: Leadership Over the Past 60 Years

This was our Leadership Horizon Conference of 2024! Click here and immerse yourself in the Highlights.

From Typewriters to AI: The Evolution of Technology and Leadership Over the Past 60 Years

As we stand on the brink of a new era in technology and leadership, it’s crucial to reflect on the journey that has brought us here. Today, personal computers and hybrid work models are standard, but the path to this reality has been filled with remarkable innovations and visionary leaders.

Celebrating 60 years of MDI’s impact on shaping and training leaders, we look back at the extraordinary changes in both technology and leadership since 1964. As Isaac Newton said, “If I have seen further, it is by standing on the shoulders of giants.” Let’s embark on a journey through time to appreciate how far we’ve come.

The Birth of the Digital Age

In 1964, while The Beatles’ “A Hard Day’s Night” topped the charts, Texas Instruments introduced the integrated circuit, marking the dawn of a new era in electronics. Baby Boomers began to integrate these new technologies into the workplace, setting the stage for the digital revolution.

The creation of ARPANET, the precursor to the internet, laid the foundation for a connected world. The 1970s witnessed dynamic shifts in leadership styles, transforming corporate culture. Personal computing emerged with Microsoft and Apple at the forefront, and by 1977, the introduction of the Apple II was revolutionizing both offices and homes.

    Leadership Horizon 2024

    Technological and Cultural Expansion

    The 1980s brought mobility and connectivity into the spotlight with innovations like the Osborne 1 and Motorola’s first mobile phone. The fall of the Berlin Wall in 1989 and the standardization of TCP/IP protocols in 1983 heralded a truly interconnected world.

    Cultural phenomena such as Star Wars captivated millions, redefining the nature of storytelling. As the new millennium approached, Google and Wikipedia transformed our access to and interaction with information. Pop culture evolved with “The Simpsons,” offering a satirical view of American life through the antics of a yellow cartoon family.

    The Digital and Data Revolution

    The introduction of the iPhone and iPad seamlessly integrated technology into daily life, showcasing the adaptability and drive of Millennials stepping into leadership roles. Platforms like TikTok are redefining media consumption, fueled by the creativity and engagement of a new generation.

    Technologies like Tesla’s Autopilot and Google’s advances in quantum computing hint at the incredible possibilities of the future. Contemporary leadership now embraces global movements for climate action, reflecting an evolving focus on sustainability and social responsibility.

    Embracing the New Era

    As we adapt to the ever-changing landscape of our world, the past six decades serve as a testament to the continuous journey of innovation and leadership. Looking ahead, it’s clear that the evolution of technology and leadership will persist, driven by creativity, adaptability, and a vision for a better future.

    As we celebrate the achievements of the past, we eagerly anticipate the exciting advancements that lie ahead, knowing that the journey of innovation and leadership continues.

    Raphaela Pouzar

    Raphaela Pouzar

    Team Assistant

    Raphaela Pouzar, a Bachelor of Business Administration student at IMC Krems, works at MDI as a marketing assistant alongside her studies. Her responsibilities include writing blog entries and creating videos in both English and German for our site.

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    Challenges and Opportunities in China

    Do you prefer to listen to this article? Click here to listen to the AI-generated version!

    Challenges and Opportunities of AI in China

    While some see China’s intensive video surveillance as a realization of George Orwell’s bleak vision of the future in “1984”, others argue that China is a safer place as crimes are quickly detected due to these measures.

    I, too, am concerned with the question of the benefits and harms of the use of artificial intelligence in public administration in China. In this blog post, I report on my experiences and observations on my recent trip to China.

    Travel preparations with hurdles

    I reactivated my WeChat account to prepare for my trip. This turned out to be more complicated than I had expected. Only after repeated attempts and several hours of effort did I manage to reactivate my WeChat account with the help of a WeChat friend from Taiwan.

    This automatically sets up the WeChat payment service Weixin Pay. I could link it to my Mastercard after scanning my passport and approving a photo using my cell phone camera. I thought to myself: now the public authorities can track my payment activities if they are interested.

    My experience with digital payment systems in China

    However, WeChat payment did not work in China and the alternative Alipay also failed to verify my credit cards. However, I did meet Germans who had success with Alipay. My attempts to communicate with my credit card processors didn’t change anything.

    To my relief, I realized that cash is usually accepted after all and that I could pay online for the high-speed train from Beijing to Shanghai with a foreign credit card. But the locals pay for everything with their phones.

    Political moods in China

    In personal interactions, my Chinese conversation partners also proved to be critical of the government. As long as people are talking and not typing virtually, they are relaxed. I mainly encountered a pragmatic attitude.
    From a transactional analysis perspective, they are treated like children by the authorities.

    However, they did not care much as long as they feel safe and can pursue their economic activities. My current view on this: The trend towards personal surveillance will continue despite attempts at regulation, and not just in China. More cameras are being used every year:

     

    • Many installed cameras by public administrations, businesses, and homeowners.
    • In addition, billions of cell phone cameras and big data analysis possibilities worldwide can monitor a large part of our lives.

    The power of surveillance: AI, resistance and political stability

    Whether in democracies, autocracies, or hybrid systems – those in political power have instruments in their hands that they can use to either benevolently or to maintain power. It is usually a combination. What seems most problematic to me is that potential resistance can be nipped in the bud. The more benevolent a system of rule is, the less resistance there will be.

    Using AI, an autocratic government can protect itself almost to the point of unassailability. However, history has proven that a lot of power corrupts. The greater the differences in power and income, the stronger the resistance.

    AI in different leadership systems

    Even the most powerful autocrats are getting older and younger people are taking over their positions. These changes are often accompanied by power struggles and thus at least temporary destabilization. AI is a new and significant aspect of the leadership system, but not the only relevant one. Other aspects are e.g:

    • Collective benefit maximization and suffering minimization for all relevant stakeholders including minorities. If an authoritarian or democratic regime achieves sustainably good results in this respect, it has a better chance of remaining in office.
    • Intelligence and education of leaders and those being led
    • Beliefs of leaders and those being led (e.g. “only the collective counts” or “it’s safer with us”)
    • The legal and executive system
    • Incentive systems and social stratification

    I also wanted to use my trip to China to further develop my views on the following 2 questions in particular:

    1. Is democracy always the best form of government?

    I remain a supporter of democracy, while at the same time maintaining the view that sometimes intelligent, benevolent autocrats can achieve better results than bad democratically legitimized governments. Over the past three decades, China has achieved amazing results in terms of prosperity, innovation, and security, for example.

    My youthful conviction that democratic systems are economically superior to autocratic ones has long been called into question by China’s one-party system. On average, however, intelligent and benevolent parties come into government more often in democracies. Above all, problematic undesirable developments can be prevented more easily and quickly.

    2. What are the benefits and harms of the new surveillance possibilities offered by AI?

    It is strange for me to see cameras even on forest paths in the Wudang Mountains. At the same time, I have rarely felt as safe at night in cities with millions of inhabitants as I do in China. In addition to security, efficiency is also a strong argument in favor of biometric recognition methods.

    I have been used to the idea for years that we are heading towards a transparent world. We are already ensuring that with our smartphones, Apple watches, etc. If we live in a society in which individual freedom and uniqueness are accepted within the harmful limits of others, transparency has little to threaten me.

    But that brings us back to question 1: if my data is being used by government agencies to maintain power or execute ideological -isms, then it may already be too late.

    Regulation with a sense of proportion

    Unfortunately, we know that even liberal democracies can become dictatorships. In recent years, in particular, there have been ominous developments in various Western countries where attempts have been made to weaken democracies through violence or manipulation.

    And we have also seen how quickly countries have become involved in wars. I therefore believe that regulation with a sense of proportion is necessary, especially when it comes to the use and storage of collected data.

    A summary of my learning journey

    For me, this learning journey was not about judging in the sense of right and wrong, but about interpreting developments in the context of history, culture, population density, religion, etc. I took one final inspiration from a leadership outcome that with me: China shows that switching to e-mobility and attractive public transportation is possible. Why are we going the other way again with combustion engines?

    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.

    • LinkedIn

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    Beyond the Horizon: GenAI and Ethical Leadership

    Beyond the Horizon: GenAI and Ethical Leadership

    by Bailey Parnell | Mar 5, 2024 | Digital Transformation, Leadership and AI, Leadership in the digital transformation | 0 comments

    Beyond the Horizon: GenAI and Ethical Leadership

    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.

    Beyond the Horizon: GenAI and Ethical Leadership

    In this blog post, keynote speaker Bailey Parnell gives us a few snippets of her exciting keynote speech at our upcoming Leadership Horizon event. We discuss the transformative role of generative AI in modern organizations, delve into how AI can boost well-being, and touch upon ethical considerations leaders must address. Enjoy reading!

    Bailey, as we approach the Leadership Horizon event on 04.04.2024, could you start by giving us a brief overview of your upcoming keynote? What can attendees expect to learn and gain from your presentation?

    My keynote at the Leadership Horizon event will delve into the transformative role of generative AI (GenAI) in modern organizations. We will explore how AI can revolutionize productivity and performance, but also how this does not need to be at the expense of wellbeing.

    Rather, there are ways that AI can support our well–being dramatically in the process. I will share the early findings of my research concerning how GenAI could and should support leadership functions and I’ll do this through the exploration of real-world applications and strategies, ethical considerations, and case studies.

    The goal is to leave attendees enlightened about AI’s potential and equip them to integrate these technologies in ethical ways that both support human well-being and performance.

    The theme of your keynote revolves around GenAI and its potential impact on organizations and individuals. Can you elaborate on the core potential and challenges of GenAI in contemporary settings, and how it connects to leadership and wellbeing?

    GenAI presents vast innovation potential, automating complex tasks, enhancing decision-making, and radically improving efficiency across various sectors. It fosters creativity, generates solutions quickly, and personalizes user experiences, all of which can lead to significant advancements in many fields.

    For example, in healthcare, GenAI can help with early disease diagnosis, personalized treatments, and accelerated drug development. However, at the same time, GenAI faces significant challenges, including ethical concerns around data privacy and consent, potential biases in AI algorithms, and the risk of job displacement due to lazy or inconsiderate leaders.

    In the same example, GenAI raises concerns about patient data privacy, consent, biases, and job displacement of healthcare workers. These challenges require careful consideration to harness AI’s potential while maintaining ethical standards fully… and our humanity.

    About leadership and well-being, I mentioned above how it can offer leaders tools to make more informed decisions, predict trends, and optimize operations, which would presumably lead to improved organizational performance. However, for both leaders and employees, it can also reduce mundane tasks and allow people to focus on more fulfilling and creative work.

    This might enhance their job satisfaction and mental well–being. Leaders have a tough job ahead. They must navigate the ethical complexities of AI, answer questions they’ve never had to answer before about humanity, and then also use these tools to support their already-existing objectives.

    The 5 most important soft skills for leaders in the age of AI

    With your background in both digital well–being research and teaching businesses the skills they need to succeed, could you share some insights on how GenAI can be harnessed to boost both organizational productivity and employee well–being simultaneously?

    My research in digital well-being and work with my learning design company have shown me many ways GenAI can significantly boost organizational productivity and employee well-being. Let’s look at 5 potential dual-intent uses for both performance and well–being (some of which we may explore again in the keynote):

    1. Automating Routine Tasks

    GenAI can handle repetitive or mundane tasks (such as report generation or scheduling). This frees employees to focus on more meaningful and creative work, thus enhancing job satisfaction and reducing burnout.

    2. Personalized Employee Training

    GenAI can tailor training programs to individual learning styles and professional development needs, which could simultaneously improve learning retention and also foster a more engaged and skilled workforce.

    3. Enhanced Decision-Making

    By providing data-driven insights and forecasts, GenAI aids in more informed decision-making, which could reduce stress and uncertainty for employees and leaders.

    4. Workplace Wellness Analysis

    GenAI could analyze workplace data to identify patterns related to stress, workload, and employee engagement, which would help organizations implement targeted wellness initiatives.

    5. Improved Communication and Collaboration

    GenAI tools can streamline communication and project management, which could lead to a more cohesive and less stressful work environment.

    The list of potentials goes on…

    Many people are concerned about the ethical implications of AI technologies. How can organizations strategically integrate AI to improve productivity and well–being while proactively addressing ethical questions associated with AI?

    I have come up with 9 ethical considerations leaders have to make when it comes to integrating GenAI in their workplaces (this may also come up in the keynote). They must work through most of these before full integration.

    At the same time, this technology is new, so be adaptable and realize things may come up that you did not intend. This is just what happens with any technological revolution. But, you can start here…

    1. Data Privacy and Security – Ensuring the confidentiality and security of employee and company data.

    2. Bias and Fairness – Addressing potential biases in GenAI algorithms and ensuring GenAI decisions are fair and non-discriminatory is crucial.

    3. Transparency and Explainability –Transparency in how GenAI systems make decisions.

    4. Consent and Choice – Respecting employee consent regarding the use of their data and providing options to opt out of GenAI monitoring or analysis, where appropriate.

    5. Impact on Employment – Considering the impact of GenAI on job displacement and the ethical implications of replacing human labor with GenAI.

    6. Mental Health and Wellbeing – Being mindful of the impact of GenAI on employee mental health and wellbeing, particularly regarding surveillance, performance monitoring, and increased expectations.

    7. Accountability and Responsibility – Clear accountability for decisions made by GenAI systems and mechanisms for redress in case of errors or grievances.

    8. Regulatory Compliance – Adhering to legal standards and regulations governing the use of GenAI in the workplace.

    9. Employee Development and Training – Addressing the need for upskilling or reskilling employees in the wake of GenAI integration.

    Promoting Cohesion and Retaining Talent

    In your keynote description, you mention that attendees will learn how GenAI will affect their specific industry and function. Can you provide some examples or insights into how different industries can leverage AI for leadership and employee well–being?

    The truth is that GenAI will affect most if not all industries eventually. I mean that.

    I have already discussed healthcare above where GenAI can assist in diagnosis and patient care. In finance, GenAI could improve risk assessment and fraud detection. For creative industries, GenAI already offers tools for design and content creation, thus freeing up time for strategic thinking and innovation.

    Every sector can leverage AI for leadership development, decision-making, and simple tasks like report-making. In addition to the examples I gave in question 3, here are some other assorted industries we can use and examples in a fun brainstorm…

    Manufacturing Industry:

    a. Performance – GenAI can optimize production lines by predicting maintenance needs and streamlining supply chain management.

    b. Employee Wellbeing – GenAI can enhance safety by monitoring working conditions and predicting potential hazards.

    Education Industry:

    a. Performance – GenAI can create personalized learning materials and curricula and adapt them to individual student needs.

    b. Employee Wellbeing – For educators, GenAI can reduce administrative burdens like grading and lesson planning, giving teachers more time to focus on student engagement and reducing work-related stress.

    Aviation Industry:

    a. Performance – In aviation, GenAI can assist in the predictive maintenance of aircraft, and optimize fuel efficiency through advanced flight path calculations.

    b. Employee Wellbeing – GenAI can also aid in managing flight crew schedules more effectively to ensure adequate rest periods and reduce fatigue.

    As you can see, this exercise could be done in any industry.

    How do you see GenAI impacting the average person’s daily life? Are there practical applications that individuals can use to make their lives easier?

    From personalized recommendations in entertainment and shopping to smart home devices that learn and adapt to user preferences, GenAI improves convenience and efficiency in the household as well.

    AI-driven apps can help people with personal budgeting, fitness routines, building resumes, and even mental health support. I have seen this first-hand in my own family with people who are otherwise technical novices and digitally illiterate. It has made their lives easier.

    As someone who has given two TED talks with millions of views, what key takeaways do you hope to leave with your audience after this keynote? How do you envision your audience feeling more confident in navigating the future of AI?

    After my keynote, I believe the audience will feel slightly uneasy, but not in a bad way. This is normal when you are suddenly able to see the eventualities of the future and the major changes that will come with them.

    However, my goal is to quell that unease with a framework for how they can approach these changes as they come, and even provoke them in responsible ways.

    I aim for the audience to feel empowered and optimistic about the future of GenAI. My goal is for attendees to leave with a clear vision of how to integrate AI into their leadership and operations confidently.

    Considering your role as the Founder & CEO of SkillsCamp and your recognition as one of Canada’s Top 100 Most Powerful Women, what personal experiences or professional milestones have shaped your understanding of the intersection between leadership, AI, and connectedness?

    I went through my existential crisis when GenAI was released to the public. The reason for my stress was not because I was stressed about how it would affect me. In fact, I am now AI-assisted in every area of my life, including the leadership of my business as a non-profit.

    Rather, I was concerned about how bad actors would use this technology and I was worried about all of the digitally illiterate people who have no idea what is coming. 

    I have been researching digital wellbeing for over a decade and I still feel like I’m only able to scratch the surface with most people and share “What is even going on here”. I snapped out of my crisis when I remembered I am better equipped than most people in the world to help humanity through this shift, given my experience, my education, and my profession.

    It gave me even more motivation to continue my research, teaching, and speaking, and to turn my non-profit into the Center for Digital Wellbeing. So, this is very personal for me now. 

    In the context of leadership, can you share any personal anecdotes or case studies where the responsible use of GenAI has had a transformative impact on an organization’s success and employee well–being?

    Easy. I can talk about my organization for this one. It has made my work better and faster. I already use GenAI, mostly ChatGPT, every day. Here are a few ways I use it to support my humanity as an entrepreneur of a learning design and development company…

    1. I have prompted ChatGPT by giving it a program overview, goals, design, methodology, etc., and said could you write me an executive summary for a proposal that is no longer than X characters. 
    2. I have told GPT the learning outcomes of a workshop on collaborative leadership and asked it to help me come up with role-play scenarios that mid-level managers could use in a workshop to practice X skills. 
    3. I have given it a set of data from a feedback form and asked it to pull the main themes from the answers with quotes for proof. 
    4. I have required leaders in leadership programs to use it as part of assignments (to prepare them for the future). 
    5. I have encouraged my staff to use it to enhance their work and make their lives easier (and I have not replaced it with more work).

    Right now, I of course double-check and edit answers for validity, accuracy, authenticity to our brand, etc. But this is just the start. I doubt I’ll even have to do that in the future. 

    Finally, what advice would you offer to leaders and professionals looking to stay ahead in the age of GenAI and connectedness? How can they prepare themselves and their organizations for the future you’ll be discussing in your keynote?

    To stay ahead in the GenAI era, leaders should embrace continuous learning about GenAI advancements and not fear change – own your role in shaping it.

    Bailey Parnell

    Bailey Parnell

    Keynote speaker and entrepreneur

    Bailey Parnell is a world-renowned speaker, theorist, entrepreneur, and pioneer in the field of digital wellbeing. At just 22 years old, Bailey was named one of Canada’s Top 100 Most Powerful Women. Since then, she has partnered with prestigious organizations like the United Nations, Deloitte, the NFL, and various governments and universities around the world to share her insights on our digital lives, generative AI, human skills development, and leadership in the future of work.

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    Did you know? Bailey will join our Leadership Horizon 2024!

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