#64 Curiosity: AI is not Magic

Dalibor Jeremić from FH JOANNEUM explains the role of AI in biomedical analysis in the podcast Neugier. Digitalization is transforming the profession toward the evaluation of complex data structures. For management in the healthcare sector, the interface with IT is becoming increasingly decisive.

AI Competence in Biomedicine: Between Professional Expertise and Technological Reality

In the current episode of the science podcast Neugier by FH Joanneum, published on October 19, 2026, Dalibor Jeremić sheds light on the interface between biomedical diagnostics and modern information technology. As a lecturer at the Institute of Biomedical Science, Jeremić provides insights into his daily professional life and the advancing digitalization in the healthcare sector. The title of the episode, AI is Not Magic, underscores the necessary demystification of technological hype in favor of a sound, scientific engagement with algorithms and data structures in medical diagnostics.

The role of the biomedical scientist has changed massively in recent years. What was once characterized by manual laboratory work is now a highly complex field in which large amounts of data must be interpreted securely. In this context, Jeremić emphasizes that while Artificial Intelligence (AI) represents a powerful tool for increasing efficiency, it always operates on the basis of human expertise and strict scientific protocols. For education at universities of applied sciences, this means a stronger integration of IT competencies into classical natural science curricula to prepare graduates for a hybrid working world.

Bridging the Gap Between Management and Specialized Science

For MBA prospects and aspiring executives in the healthcare sector, this discourse provides important points of reference. The discussion makes it clear that digitalization projects in the medical field lead to success not through technical investment alone, but primarily through a subject-specific understanding of processes. Managers wishing to occupy interface positions in clinics, pharmaceutical companies, or laboratory groups must understand the limits and possibilities of AI without misunderstanding it as a universal solution. Classifying AI as a tool rather than magic demands realistic budgeting and strategic planning that places people and data quality at the center.

Relevance for the MBA Market in the DACH Region