![[Artificial Intelligence] AI beyond the buzzword - How AI reshapes companies’ workforce strategy](https://images.spr.so/cdn-cgi/imagedelivery/j42No7y-dcokJuNgXeA0ig/ce760182-b481-4df6-af32-475934ca35c2/gradients_10/w=1920,quality=90,fit=scale-down)
📌 Key facts
- Uncover Real-World AI Impact: Go beyond the buzz and examine how emerging AI technologies—like advanced language models—are transforming companies’ operations, decision-making, and job tasks right now.
- Analyze Shifting Skill Demands: Use comprehensive occupational data to pinpoint which skills are becoming more valuable, which roles are changing most, and how employees can best adapt.
- Provide Actionable Roadmaps: Deliver clear recommendations for businesses, policymakers, and individuals on navigating the rapidly evolving AI landscape—ensuring resilient strategies and workforce readiness.
- When: Ideally start before April 2025, but flexibility is possible. Applications are open now!
- How to apply: Send us an e-mail (at the end of this page) with your CV, a grade report, and a short bullet-style thesis proposal.
- 📌 Key facts
- 💡 Background
- 🎯 Goals
- 🎓 Profile
- 📚 Further Reading
- 📄 Requirements to work
- 📝 How to Apply
- 📬 Contact
- 🦾Who We Are
💡 Background
The rapid rise of Artificial Intelligence - particularly generative models - has propelled industries into a new era of automation, innovation, and strategic realignment.
- Catalyst for Change: Tools like ChatGPT, generative image models, and advanced data analytics are no longer just buzzwords; they’re reshaping business operations, consumer experiences, and entire job categories.
- Opportunities & Challenges: While AI has opened doors to efficiency gains and creative solutions, it also raises questions about which tasks remain uniquely human, which can be augmented by AI, and which may disappear altogether.
- Revisiting the Data: By leveraging data on jobs, tasks, and artificial intelligence capabilities, we can compare predictions from several years ago with today’s reality - shedding light on what skills remain to be required and which ones are likely to disappear in tomorrow’s jobs.
🎯 Goals
Aiming to build on the foundation of Frey (2017) we want to understand how recent advancements in AI - particularly generative models - are reshaping work at both the firm and workforce levels.
- Leverage Existing Data: Extend the analysis using Frey’s original dataset (e.g., O*NET occupational data) to capture changes in job tasks and requirements.
- Empirical Examination: Quantitatively evaluate the impact of new AI applications on job displacement, augmentation, or invariability.
- Thesis Outcome: Provide updated insights and actionable recommendations for organizations and policymakers, highlighting shifts in AI’s real-world impact.
🎓 Profile
We seek a TUM EMBA, master, or bachelor student excited about cutting-edge research on emerging technologies and their business impact.
- Enrolled in an bachelor’s, master’s or executive MBA program at TUM, such as Management & Technology, Data Science, Informatics, or Economics.
- Interest in empirical methods (e.g., econometrics, data analysis, or machine learning).
📚 Further Reading
Your research will build upon Frey (2017) while integrating the latest perspectives on AI and employment.
- Frey & Osborne’s approach to using occupational data for technological susceptibility analysis: Frey, C.B., Osborne, M.A.: The future of employment: How susceptible are jobs to computerisation? (2017), Technological Forecasting and Social Change, 114, pp. 254-280
- Recent scholarly and industry reports on generative AI’s impact on specific tasks, industries, and skills (e.g., Dell'Acqua et al. 2023, McKinsey & Company 2024, etc.)
📄 Requirements to work
We do not want your research to gather dust in some corner of bookshelf but make it accessible to the world. Thus, we warmly encourage you to create some or all of the following:
- Slide Deck - summarize your research and possibly present it
- 2 LinkedIn-Posts about the most important findings and summarizing the topic
Please note that these deliverables are not officially required.
📝 How to Apply
If you are interested, please contact Philipp Lemanczyk by submitting your CV and grade report. Please also briefly outline your tentative research idea (research question, data and methods, possible outcomes with a tentative outline all in a Word or PDF - bullet points only)
We're greatly looking forward to hearing more about you!
📬 Contact
Philipp Lemanczyk (Chair for Strategy and Organization)
Please add the following subject in your email: “Application-AI-workforce” and your name
🦾Who We Are
Philipp Lemanczyk is a PhD student at the Chair for Strategy and Organization focusing on Information Systems and Entrepreneurship research. Before embarking on his PhD journey, he worked at McKinsey & Company as a consultant focusing on strategy, organizational & digital transformation, and M&A. He holds a M.Sc. in Mechanical Engineering, a B.Sc. in Mechanical Engineering, and a B.Sc. in Industrial Engineering from TU Darmstadt.
The Chair for Strategy and Organization is 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. Topics such as Agile Organisations and Digital Disruption, Blockchain Technology, Creativity and Innovation, Digital Transformation and Business Model Innovation, Diversity, Education: Education Technology and Performance Management, HRTech, Leadership, and Teams.. We are always early in noticing trends, technologies, strategies, and organisations that shape the future, which has its ups and downs.