Leadership development is no longer just a buzzword, but plays a central role in a digital and technology-driven working world. KIROI Step 9 is about how managers can be strengthened by specifically developing AI skills. Whether in production, healthcare or IT - more and more decision-makers are looking for ways to successfully integrate not only traditional management, but also data-driven decision-making, automation and innovation management into their day-to-day management.
Many companies are faced with the challenge of reducing existing uncertainties and actively shaping digital transformations. Clients report that they are learning in workshops and coaching sessions how to use AI in a targeted manner - whether to optimise supply chains, support medical diagnoses or manage complex IT projects. Transruption coaching helps companies and managers to systematically drive this development forward in important projects and anchor a sustainable management culture.
Why leadership development through AI expertise is so crucial
Today, leadership development is no longer only organised through traditional seminars or formal training courses, but also includes informal learning formats such as coaching, mentoring and learning on the job[1]. Particularly in the context of artificial intelligence, the development of managers requires an individualised approach that focuses on both professional and personal development.
Manufacturing companies, for example, are developing targeted workshops in which teams learn how AI technologies can make existing processes more efficient. In the healthcare sector, managers often address the question of how AI-based diagnostics can be meaningfully embedded in everyday clinical practice. And in the IT sector, the focus is on questions relating to AI-supported project management and the integration of autonomous assistance systems.
A key aspect is that leadership development is not seen as a one-off, but as a continuous process. Companies that rely on an integrated concept often find that their managers are more confident in dealing with new technologies, can network their teams better and drive innovation[2].
Procedure and methods at a glance
The development of managers focussing on AI skills follows a clear framework. First, individual and organisational needs are analysed, for example through employee interviews, 360-degree feedback or targeted surveys. This forms the basis for customised development plans that combine face-to-face and online formats, such as online modules, peer coaching and interactive workshops[3].
The implementation usually takes place in several steps: After each learning unit, participants put what they have learnt into practice in their day-to-day work, reflect on their experiences and receive feedback. This combination of theory and practice is crucial because it makes real challenges visible and enables the application of AI expertise to be experienced directly[5].
Evaluation involves regularly reviewing the learning success. Companies often use feedback loops and defined KPIs to visualise and continuously improve the impact of management development measures[5].
Practical examples: How managers develop AI expertise
Digital skills are not an end in themselves, but help to optimise business processes and drive innovation. Companies in the mechanical engineering sector, for example, use AI-supported maintenance predictions to minimise downtimes. Managers in production learn how to use data analyses to control production processes and thus use resources more efficiently.
In order to promote the development of hybrid teams, many organisations rely on targeted further training in which managers test how they can motivate and manage virtual and face-to-face teams in equal measure. Training and coaching help them to overcome uncertainties and promote an open learning culture[3].
The automotive industry also shows how important leadership development is in the context of AI: here, decision-makers integrate assistance systems into their day-to-day work in order to make complex decisions based on data. At the same time, ethical issues and transparency are at the forefront because AI applications must be used responsibly[4].
Tips for successfully integrating AI into management development
Utilise internal networks: Experienced managers can act as mentors, but younger employees can also provide valuable impetus as „reverse mentors“, especially when dealing with new technologies[9]. This creates a mutual learning process that strengthens the entire organisation.
Rely on customised formats: Combine face-to-face events with digital learning modules to respond flexibly to individual needs. A workshop can be just as valuable as targeted coaching or a job rotation to gain insights into different areas and provide holistic leadership[3][1].
Create space for reflection: regular exchange formats - for example in the form of peer counselling or moderated discussion groups - help to identify challenges, develop solutions together and sharpen your own attitude. Leadership development is not a one-way process, but thrives on dialogue.
BEST PRACTICE with one customer (name hidden due to NDA contract) A multi-stage programme to promote AI skills was developed in a medium-sized technology group. Following a needs analysis based on employee interviews and surveys, the managers started with a basic module on AI technologies. This was followed by workshops in which specific use cases from the company were worked on - such as the automation of reporting processes or the introduction of AI-based assistance systems in customer communication. After each module, the participants were given tasks for their day-to-day work, which they reflected on in the next workshop. The programme was accompanied by individual coaching that specifically addressed the challenges faced by each manager. After completing the programme, the participants reported a significant increase in self-confidence in dealing with new technologies, better networking between the teams and increased innovative strength within the company. The evaluation showed that the management development had brought about lasting changes in behaviour and that the company is better prepared for future technological upheavals.
Consider risks and ethical aspects
Management development must also focus on responsibility in dealing with AI. Questions about data protection, transparency of algorithms and possible discrimination through AI systems are key[4]. An open culture of discussion within the company helps to address critical issues at an early stage and create an awareness of ethical risks.
Guidelines and governance concepts provide orientation on how AI can be used responsibly. During their development, managers should learn how to implement control mechanisms and openly address uncertainties within the team. After all, only those who create trust can successfully shape digital transformations.
My analysis
Leadership development through the development of AI expertise is not a trend, but a key factor for the competitiveness of companies in all sectors. Those who invest not only secure the future viability of the company, but also initiate innovation processes and create an agile management culture.
The combination of traditional leadership training with modern, technology-driven approaches is critical to success. Targeted programmes that enable individual learning paths, integrate practical applications and promote continuous reflection achieve sustainable effects. Transruption coaching helps companies to master this challenge, reduce uncertainty and establish a learning culture in which innovation can flourish.
Ultimately, leadership development is not a one-off project, but an ongoing process that changes the entire organisation. Companies that follow this path report more dynamism, better collaboration and a high level of adaptability to digital change.
Further links from the text above:
Methods of leadership development - Forum Verlag [1]
Leadership development through AI competence - transruption coaching [2]
Leadership development: Methods and effective tools - Haufe Akademie [3]
AI for managers: AI demands new leadership skills - Haufe Akademie [4]
Measures and concepts for leadership development - Brainershub [5]
Leadership development - concept, methods, definition - Rainmakersociety [9]
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