📌 Key facts
- What: This thesis explores the effect of Transformational leadership (TFL) on AI adoption using the UTAUT framework.
- When: Start anytime soon. Applications are open!
- How to apply: Send your CV, transcript of records, and max. 5 sentences why this topic interests you (more details below)
💡 Background
Organizations across industries are increasingly introducing AI-based tools, yet implementation success ultimately depends on whether employees adopt and use these systems in their daily work. A widely used lens to explain such adoption is the Unified Theory of Acceptance and Use of Technology (UTAUT), which highlights four key determinants of technology acceptance: performance expectancy, effort expectancy, social influence, and facilitating conditions (Venkatesh et al., 2003). While UTAUT specifies what drives use, it says less about how these perceptions are shaped inside organizations during periods of technological change.
This is where leadership comes in: by shaping employees’ interpretations of AI’s usefulness and ease of use, reinforcing shared expectations about adoption, and ensuring adequate support and resources, leaders can influence the key UTAUT conditions for sustained AI use. In particular, transformational leadership (TFL) may be especially relevant because it helps create meaning around change, reduces uncertainty, and strengthens enabling conditions. However, systematic work that tightly integrates UTAUT with TFL to explain these AI use dynamics remains limited.
🦾Who We Are
I am a PhD student and Senior Consultant at McKinsey & Company. My research interest lies broadly in the human dimensions of AI, including its adoption, effective use, and its impact on workplace dynamics. I have an educational background in Business and Information Systems Management.
As Chair for Strategy and Organization we are focused on research with impact. This means we do not want to repeat old ideas and base our research solely on the research people did 10 years ago. Instead, we currently research topics that will shape the future such as Quantum/Deep Tech, (Generative) Artifical Intelligence, Digital Transformation and Business Model Innovation, Diversity, Education Technology and Performance Management, Leadership, and Teams. We are always early in noticing trends, technologies, strategies, and organisations that shape the future, which has its ups and downs.
🎓 Profile
- Strong interest in AI, digital transformation, and organizational development
- Reliable, structured, and self-driven working style
- Strong academic record and analytical mindset
📝 How to Apply
If you are interested, please contact Lisa-Maria Schober by submitting your CV, grade report, preferred starting date & short motivation statement (max. 5 sentences) Please also indicate which kind of thesis (= outcome) you are interested in.