This master thesis offers a unique opportunity to delve into the transformative world of Artificial Intelligence (AI) and its influence on employee efficiency. As a rapidly evolving field, AI presents a plethora of ways to enhance efficiency and effectiveness in the workplace. This research aims to empirically investigate how AI tools and technologies are reshaping various business processes and tasks, measuring their impact on efficiency & productivity levels across different industries. You will have the flexibility to choose your specific research method and approach, ideally leveraging a cooperative partner for practical insights. This thesis is not just an academic exercise but a journey to contribute meaningfully to the cutting-edge discourse on AI and the future of work. If you're passionate about understanding the nexus of technology and workforce efficiency, this thesis is your gateway to making a significant impact in the field.
Who? Only master thesis supervisions are possible for this topic.
When? Applications are open – start anytime.
How to apply? Send us an e-mail (at the end of this page) - see here more information on what should be included in the email
💡 Background
Artificial Intelligence (AI) is a game-changer in the realm of business efficiency, significantly enhancing employee efficiency & productivity. Its applications range from automating routine tasks to providing advanced analytics for strategic decision-making. This thesis invites you to delve into how AI technologies are reshaping the workplace, boosting efficiency, and transforming the way we approach work tasks.
🧠 Your Mission:
Embark on an empirical research journey to explore the multifaceted impact of AI on employee efficiency / productivity. This is a unique opportunity to combine theoretical understanding with practical insights, ideally leveraging your current workplace as a supportive partner.
🔍 Research Flexibility:
Choose your specific research method and approach – whether it's case studies, surveys, or data analysis. Tailor your thesis to explore various dimensions of AI's impact in a corporate setting.
🌐 Why This Matters:
This isn't just academic research; it's a deep dive into understanding and shaping the future of work. By analyzing AI's role in enhancing efficiency / productivity, you'll contribute to a critical discourse on technology and workforce efficiency.
📚 Are You Ready to Explore?
If AI and its potential to revolutionize the workplace excite you, this master thesis supervision is your gateway. Let's embark on this enlightening journey together to uncover how AI is setting new standards in employee efficiency / productivity! 🚀
🦾Who We Are
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 Organizations and Digital Disruption, Blockchain Technology, Artificial Intelligence, 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 organizations that shape the future, which has its ups and downs.
My personal research area focuses on exploring how AI can enhance company-internal productivity and improve work quality for effective decision-making in large-scale and transnational organizations. This interest stems from my diverse experiences, including my studies at Columbia University and UCSB, my roles at the UN Secretariat and Airbus, and co-founding BoxOrganizer, all of which have provided a rich backdrop for understanding the transformative potential of AI in business and technology management.
🎯 Goals
Your primary objective will be to conduct a comprehensive empirical study on AI's influence on employee efficiency / productivity. This research will enable you to become a well-versed scholar in this field, bridging the gap between theory and practice, and contributing to a better understanding of AI's role in modern business environments.
📚 Further Reading
Further readings in this field:
- Davenport, T. H. (2018). The AI Advantage: How to Put the Artificial Intelligence Revolution to Work. MIT Press.
- Daugherty, P. R., & Wilson, H. J. (2018). Human + Machine: Reimagining Work in the Age of AI. Harvard Business Review Press.
- Deming, D. J., & Noray, K. (2020). STEM careers and the changing skill requirements of work. Journal of Labor Economics, 38(S2), S305-S341.
- Moore, P. V. (2022). Artificial Intelligence at Work: The Impact of AI on the Future of Work. Publisher.
- Park, Y., Forte, A., & Diakopoulos, N. (2020). A taxonomy of AI-driven content moderation. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-13.
- Siegel, E. (2016). Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Wiley.
- Tambe, P., Cappelli, P., & Yakubovich, V. (2020). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 62(4), 5-20.
- Wang, D., & Wang, P. (2020). Big data analytics in human resource management: A review and future research agenda. Computers in Human Behavior, 107, 105414.
- West, D. M. (2018). The Future of Work: Robots, AI, and Automation. Brookings Institution Press.
- Wingard, J. (2020). AI-Powered Workforce: How Artificial Intelligence, Data, and Messaging Transform Modern Business. Columbia Business School Publishing
📝 How to Apply
If you are interested, please contact Nicolas Leyh (click the button to email below) 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). Please also briefly outline your tentative research idea (research question, data and methods, possible outcomes with a tentative outline all in word as *.docx)
We're greatly looking forward to hearing more about you!
📬 Contact
Nicolas Leyh (Chair for Strategy and Organisation)
👉 nicolas.leyh@tum.de