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KIROI - Artificial Intelligence Return on Invest: The AI strategy for decision-makers and managers

Start » KIROI Step 9: Leadership development through AI expertise

17 August 2025

KIROI Step 9: Leadership development through AI expertise

Digital Leadership Digital transformation HR work and Teams 4.0 Artificial intelligence

Leadership development is more crucial than ever for sustainable business success. In particular, the integration of AI competence is gaining increasing importance, as it helps leaders to actively shape digital transformation processes and position their teams for the future. In this article, we will shed light on how targeted leadership development can succeed through the expansion of AI competence, and what practical examples and methods can support this.

Leadership Development in the Age of Artificial Intelligence

Modern leaders face the challenge of developing technological competencies alongside traditional management skills. The ability to understand, evaluate, and strategically implement AI technologies is key to professional success. Leaders thus become important drivers of digitalisation by using data analysis for informed decisions and promoting innovative automation.

For example, leaders in manufacturing companies learn how AI optimises supply chains or makes production processes more efficient. In healthcare, the use of AI-based diagnostics enables better patient care, while in the IT sector, AI-powered project management tools contribute to increasing team productivity. In this way, leaders are empowered to fulfil their responsibilities in the digitalisation process in various contexts and industries, while simultaneously fostering an innovation-friendly corporate culture.

BEST PRACTICE with one customer (name hidden due to NDA contract) A medium-sized technology company introduced a comprehensive programme to enhance the AI expertise of its managers. Through workshops and individual coaching, participants were supported in identifying and meaningfully utilising AI applications. This guidance made managers feel more confident in digital transformation and increased the acceptance of new technologies within the teams.

Methods of leadership development with a focus on AI

A successful leadership development programme combines various formats to optimally support learning processes. Classic seminars and workshops provide foundational knowledge on AI and its applications. Coaching and mentoring provide individual support to leaders by specifically addressing personal challenges in dealing with AI. Learning on the job enables practical experience by having leaders implement AI projects in their daily work.

Practical examples illustrate the benefits of these methods:

A leader in the finance industry uses 360-degree feedback to encourage self-reflection and improve their handling of AI-powered analytics tools.
In medium-sized companies, job rotations enable managers to gain exposure to different areas of AI application, thereby developing a more comprehensive understanding.
Action Learning groups collaboratively work on AI projects, which strengthens problem-solving skills and promotes exchange among leaders.

Practice-oriented coaching as support

Transruptions-Coaching sees itself as a supportive force for projects focused on executive development. It guides executives in developing individual solutions and reducing uncertainties when dealing with AI. By providing impulses and facilitating reflective conversations, coaches create a safe space for exploration and sustainable learning.

In the IT sector, for example, executives benefit from coaching that teaches how to handle AI-supported data analysis. In the automotive industry, it helps to steer digital change processes and involve employees. In the service sector, coaching in turn supports the development of AI-based customer dialogue systems to increase service quality.

AI expertise as a basis for future-oriented leadership

Leaders must not only understand AI, but also use it responsibly. Leadership development therefore also includes topics such as transparency in algorithmic decisions, ethical aspects of AI use, and data protection. This builds trust and promotes acceptance among employees.

A manufacturing company, for example, implemented control mechanisms to make AI-based decisions traceable. In a clinic, managers were trained on how to address ethical questions related to AI within teams. In the marketing department, managers ensure the use of data protection-compliant AI solutions to handle customer data responsibly.

My analysis

Leadership development today is inextricably linked with the expansion of AI expertise. Systematic training enables leaders to specifically leverage the potential of digitalisation and successfully steer their organisations through change. Practical examples from various sectors show that individual guidance, structured programmes, and the delegation of responsibility are key success factors.