The education and training of managers has gone through various phases in the past. At present, the negative consequences of too narrow a focus on theory are becoming increasingly clear and the idea of management as a dynamic profession that combines theory and practice is emerging. At the same time, artificial intelligence (AI) is changing learning and management education. Key drivers of this evolutionary change are disruptive learning ecosystems that are challenging the traditional players. The journey into this near future begins with an outline of the current patterns of success for a career in management.

In this new article in our series of blog posts on AI, I look at the present and future development of management education, in which artificial intelligence plays an important role.

Success patterns for a management career

In past decades, the proven success pattern for a turbo career in management consisted of the following steps:

• Bachelor’s degree in engineering or information technology
• short orientation phase in a reputable company
• MBA at a renowned business school
• further years of training in consulting, investment banking or private equity
• change to a staff unit for corporate development and
• rapid promotions on the way to management level.

However, this pattern of success is associated with two obvious disadvantages:

1. The limited work-life balance in professional services companies, which are considered to be labor-intensive, and
2. the cost barrier of MBA programs at well-known business schools.

For example, the cost of a one-year MBA course at one of Europe’s elite universities is between 80,000 and 100,000 euros. Added to this is the high cost of living at locations in metropolitan regions. In the USA, where most MBA programs last two years, the costs, including accommodation and health insurance, can add up to 250,000 euros.¹ Applicants must therefore carefully consider whether such an investment and the associated loss of income is worthwhile.

In addition, starting in the USA and with a considerable delay, a second pattern of success has also emerged in Germany, albeit one that is associated with even greater risks. This path leads from an idea to the founding and scaling of a start-up. The players are usually creative, interdisciplinary teams that work on new business models with great commitment. A characteristic of successful founders is that they are also deeply involved in details and are familiar with important processes. There has long been no shortage of such talent in Germany, but there are deficits in the innovation policy framework. The situation has improved in recent years. But there is still a lot to be done.

One reason for the success patterns outlined above is that management science has become increasingly open to the technical sciences. Training in traditional engineering and the newer information technology qualifies students for a specialist career. However, a management career also requires skills in strategy, innovation, marketing, production, finance, organization and personnel management. An interdisciplinary management course teaches all of this. In addition, management education trains the skills that link to the technical sciences. An important field of application is the design of new business models.²

The pioneer of this development in Germany is the University of Stuttgart, where I have been teaching as an honorary professor since 1994 following my external habilitation. In Stuttgart, the technical-oriented business administration course was introduced as early as 1974, thus focusing on the connectivity of business and technology. The following diagram illustrates the segmentation of disciplines.

Less obvious than these patterns of success is a shift in focus in the content of management education and training. This development affects both business schools and traditional technology and business-oriented courses. One important point of criticism is their excessive focus on theory.

Too strong a focus on theory and its consequences

In an article published in the Harvard Business Review in 2005, the renowned US professors Warren Bennis and James O’Toole criticize a misguided development at American business schools. Triggered by funding from foundations, a stronger emphasis on scientific rigor in the form empirical treatment of relatively limited issues began there at the end of the 1950s. Publication in scientific journals became decisive for a career as a professor. Practical experience and the relevance of research fell by the wayside, playing an increasingly minor role in appointments^(3.

Unfortunately, the same development has been taking place at German universities for a long time. The result is a series of negative consequences:

• Teaching has become less important than research
• the professors bring less practical experience to their teaching and research
• there are hardly any up-to-date textbooks, especially in dynamic subjects such as innovation management
• research is dealing less and less with complex topics of practical relevance that are difficult to access using empirical methods
• the target audience for the results of this research is primarily other researchers, while practitioners rarely read articles from scientific journals
• many graduates are not immediately employable as project managers in demanding practical projects, even after completing a doctorate.

The major beneficiaries of this development have long been management consultancies and the consultants working there, who fill the gap left by business schools and universities. These winners distinguish themselves with their ability to tackle new, complex problems in a practice-oriented manner. As a result, consulting has become an important next step in professional development and a career accelerator. For clients, this causal chain has unfortunately increased their dependence on consultants.

It is astonishing that this development has not yet been analyzed and evaluated more critically by corporate practice. We therefore want to explore the question of what an approach to improvement could look like. To do this, management would have to transform itself into a dynamic profession.

Management as a dynamic profession

The education and training of managers is characterized by the three dimensions of theory, practice and the dynamics of change. Particular challenges lie in the combination of theory and practice as well as the increasing dynamics of the corporate environment. The idea of management as a dynamic profession is based on the development of management education and training.

This development has taken place in various phases. The emergence of management as an interdisciplinary field has a long history. The success of many German hidden champions in recent decades and also the phenomenal rise of digital companies from the USA is primarily based on managers with the ability to combine technical and business expertise.

The early degree programs made an important contribution to this connectivity in the first phase. With their pronounced focus on practice, prospective managers were very well prepared for the challenges of working in organizations. This phase could be placed under the motto of the great social psychologist Kurt Lewin: „Nothing is as practical as a good theory“. This implies that an excellent professor can be expected to have extensive practical experience in addition to academic achievements.

In a second phase of management education, the academization already outlined took place in the sense of restricting research to empirical approaches for dealing with limited issues. The majority of dissertations and habilitations now follow this path, which rarely leads to far-reaching management innovations.

Today, new impetus usually comes from professors who are also active in executive education and consulting or even as company founders. The results are often published in practice-oriented journals such as the Harvard Business Review and books by international publishers. Although this type of professor is in the minority in terms of numbers, they make a significant contribution to innovations in management theory.

A reorientation of management education is emerging in a third phase. This phase takes account of the highly dynamic nature of change and creates a stronger link between theory and practice. The result is a management that sees itself as a dynamic profession. The aim is to create innovative content for research and teaching in order to meet the many new challenges.

The following are important criteria for management activities to become a profession:

• Qualified training with a degree
• practical experience with demanding tasks
• ethical standards and possibly also
• a form of regulation, e.g. of AI.

In this respect, management’s claim to be a profession is currently only partially fulfilled. However, management can learn from other application-oriented sciences such as medicine.

Learning from medical training

No sensible person would allow themselves to be treated by a doctor with little practical experience who has never worked in a hospital. In order to ensure that medical training is not just theoretical, chief physicians at renowned clinics often work as professors at universities alongside their practical work. Part of the training takes place in teaching hospitals and overall the system of universities and clinics is much more permeable than the training and further education of managers.

The more practice-oriented universities and the dual study programs offered by private business schools do offer an alternative to studying at universities. However, most providers only have a limited right to award doctorates. This means that the contribution made by doctoral students to research is largely missing.

In view of the universities‘ strong desire to maintain their position, the best that can be expected from them in management education and training is change in small steps. A first step could be to integrate theoretically qualified managers and their companies much more closely into teaching and research. A long-established approach to this is action research.⁴ This involves interdisciplinary teams designing innovative practical projects, publishing the results and making them accessible for teaching purposes. This has long been a common approach in management consulting. Both theoretically oriented professors and practitioners would benefit from such cooperation between universities and companies.

One exciting question now is what new impetus for management education will come from artificial intelligence (AI).

AI is changing management education

According to a study by the British „Times Higher“ magazine, thirteen of the world’s best AI universities are in the USA, three in the UK, two in China, one in Switzerland and one in Singapore. So there is still „room for improvement“ for the countries of the European Union. Chinese companies see 2025 as a key year for AI applications. This is why China is increasingly focusing on specific industry models in addition to large language models.⁵ This is a strategy that Germany could learn from.

In addition to industry-specific models, AI is also becoming increasingly important for training and development. Almost all companies are faced with the challenge of upskilling and reskilling their employees successfully and cost-effectively.

This also applies to management training and development. AI has a profound impact on four aspects of management. It changes:

• Research and teaching as well as learning technologies
• all functions and business processes of organizations
• all economic sectors and the public sector as well as
• management as a developing profession.

The practical skills of managers and employees who use AI as a tool are of great importance here.

Engineering and management courses are now facing the challenge of integrating the fundamentals and applications of artificial intelligence into their curriculum. The learning content is developing very dynamically and individual professors therefore often feel overwhelmed by this integration task. According to the European Union’s AI Act, companies are obliged to train employees who use AI systems in how to use them. Many companies are not yet aware of this. In July 2024, the German association Bitcom asked German managers about their attitude towards AI. According to the survey⁶

– 29% of respondents are cautious and 16% skeptical, but still
– 46% are keen to experiment and 9% are even enthusiastic.

Artificial intelligence is therefore both a learning content and a learning tool that is changing university teaching and practice.

In this context, it is remarkable how dynamically learning technologies have developed over the past two decades. We therefore want to take a look at the possible future of corporate learning.

Development towards AI-based corporate learning

Since the turn of the millennium, the development of learning technologies used by organizations has gone through the following four phases:

1. E-learning with Learning Management Systems (LMS) as a platform
2. further development of the LMS into a more competence-oriented learning in the sense of a personnel development system
3. digital microlearning with Learning Experience Platforms (LXP) and the increasing importance of videos, as well as
4. AI-based learning platforms that generate individualized content relatively independently.

In each of these phases, LearnTech providers have disappeared from the market and new ones have emerged. Providers that rely on AI include Absorb, Arist, Docebo, Growthspace, LearnUpon, Sana Labs, Uplimit and Work Ramp⁷

Planning the use of learning technologies in organizations is often not done top-down, but bottom-up by HR management and information technology. Cooperation with start-ups plays an important role here

The young Berlin-based company Doinstruct uses AI to train „desk-less“ employees. Gartner estimates this target group at 2.7 billion people worldwide. It is twice as large as the number of people who work at a desk. The company uses AI to generate short educational videos for „frontline workers“, who often have neither a laptop nor an email address. So far, Doinstruct has produced more than 250 training videos. Companies can personalize this offer. The basis for the generated videos is provided by well-known AI providers. Doinstruct’s experts select the content and scriptwriters prepare it. The company has developed software that sends the log-in via SMS. WhatsApp chats are also being considered. The content is translated into 25 languages.⁸

Procedure for AI-supported learning in management

The Doinstruct example shows what AI-supported learning in management can look like. It consists of seven steps that are adapted to the respective situation.

The first step is an AI-supported summary of existing learning content. This step requires prompting supported by reasoning models and a critical analysis of the AI-generated content. It is not intended to replace teachers, but above all to increase their productivity.

In step two, project-oriented action learning by universities and companies creates innovative, practice-oriented learning content. In this way, new knowledge and skills are incorporated into teaching.

The third step is about combining the basics with new content and structuring it into microlearning. These short sequences enable the modularization of learning programs.

A multimodal, didactic preparation is then the task of step four. In this way, a professional combination of text, sound and image is achieved, which is combined with practical exercises. These first four steps can be used for specific management disciplines and industries.

In the fifth step, there is the option of AI-supported individualization of the learning content. This allows it to be adapted to the specific situation of a company and individuals.

In the sixth step, innovative learning technologies are used to further develop learning platforms that enable scaling. Most companies will master this step together with LearnTech partners.

This lays the foundation for step seven, which focuses on AI-supported continuous improvement. Disruptive learning ecosystems play an important role in the implementation of such an approach.

Change through disruptive learning ecosystems

A disruptive learning ecosystem is a network of partners from politics, science, business and the learning community whose disruptive effect comes from innovative approaches and barriers that are difficult to overcome by traditional players.⁹ One advantage of the emerging AI-based stakeholder ecosystems is better cooperation between the partners.

Such a learning ecosystem consists of the following players:

• Politics that create a framework that promotes innovation
• universities, consultants, trainers and authors who conduct research and offer learning content
• traditional and innovative education providers that market learning content
• AI and LearnTech providers who design learning platforms and
• organizations and individuals in the dual role of customer and provider of learning content and data.

The opportunity for a more resilient Europe lies in taking a pioneering role in such new educational systems with trustworthy AI solutions. The goal is connective management education for the changing world of work in the AI age.

Connective management education for the AI age

An important characteristic of the fifth development stage of connective strategic management ¹⁰  is personnel development that takes into account the specific requirements of the changing world of work in the AI age. This connective management education combines elements in the following fields:

• Theory and practice (A)
• training and further education (B)
• specialization and interdisciplinarity (C) and
• human strengths and artificial intelligence (D).

The harmonization of these elements is an important design approach within the framework of Strategy 5.0, which enables new competitive advantages. The basis for this is a changed attitude that is characterized by a future-oriented spirit. Such an attitude combines optimism with openness and curiosity with the joy of experimentation to create a mental agility that helps to recognize and exploit opportunities.¹¹

The first of these four fields is a better combination of theoretical principles and their practical application. This involves both training for a changed world of work and the further training of many people in a world of work that is changing as a result of AI. AI is giving rise to new professional specializations. At the same time, the importance of a more interdisciplinary approach to management education is increasing. Overall, it is important to combine human strengths in teaching and research, such as a forward-looking approach, with the use of AI as a tool.

This fourfold connectivity has now become one of our focal points in research, teaching and consulting.

Conclusion

• Universities should strive for a stronger link between theory and practice in the education and training of managers. Medical training provides inspiration on the path to management as a dynamic profession
• Artificial intelligence (AI) is not only changing the world of work, but also management education. AI is both a learning content and a tool
• LearnTech providers and user companies are working on AI-based learning platforms, which are the focus of a new development phase in corporate learning
• Disruptive learning ecosystems challenge traditional players, but also represent an opportunity to realign the European education system
• Connective management education for the AI age combines elements in various fields.

Literature

[1] von Elm, K., Beware of lofty expectations. In: Handelsblatt, March 07/08/09, 2025, p. 36-37

[2] Servatius, H.G., Evolution of strategic management. In: Competivation Blog, 28.06.2024

[3] Bennis, W.G., O´ Toole, J., How Business Schools Lost Their Way. In: Harvard Business Review, May 2005, pp. 96-104

[4] Servatius, H.G., Generative AI and Mass Customized Action Learning. In: Competivation Blog, 28.08.2023

[5] Bomke, L., Gusbeth, S., Who will win the AI race? In: Handelsblatt, March 10, 2025, p.18

[6] Burkhardt, K., Anyone working with AI systems must be trained beforehand. In: Handelsblatt, March 18, 2025, p. 26-27

[7] Bersin, J., The $ 340 Billion Corporate Learning Industry is Poised for Disruption, March 23, 2024

[8] Schimroszik, N., Doinstruct trains employees with AI. In. Handelsblatt, March 19, 2025, p. 27

[9] Servatius, H.G., Designing innovative stakeholder ecosystems. In: Competivation Blog, 10.01.2023

[10] Servatius, H.G., Strategy 5.0 for mastering the new challenges. In: Competivation Blog, 28.06.2022

[11] Pferdt, F.G., Radikal besser – Entfache den Zukunftsgeist, der in dir steckt, Hamburg 2025