This master thesis presents a compelling opportunity to explore the return on investment (ROI) of Artificial Intelligence (AI) in business environments. In a world where AI is rapidly reshaping industries, understanding its financial impact is crucial. This research will empirically analyze how AI investments translate into tangible business benefits, ranging from cost savings to revenue generation. You will have the autonomy to choose your specific research methodology, ideally partnering with a corporation to gain real-world insights. This thesis goes beyond theoretical analysis, offering a chance to contribute to critical discussions on the economic viability of AI in modern business.
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
In the evolving landscape of business technology, AI stands out as a significant investment with the potential to drive transformative changes. From automating processes to optimizing decision-making, AI’s applications are vast. This thesis challenges you to investigate the economic outcomes of these investments, focusing on their profitability and long-term value in various business scenarios.
🧠 Your Mission: Engage in an empirical study to quantify the ROI of AI implementations in the business sector. This research is an opportunity to bridge theoretical knowledge with practical financial analysis, potentially in collaboration with your current workplace or another corporate partner.
🔍 Research Flexibility: You may choose from various research methods, such as:
- Cost-Benefit Analysis: Evaluate the financial costs against the gains brought by AI.
- Comparative Case Studies: Compare businesses with and without AI investments to assess the financial impact.
- Performance Metrics Analysis: Analyze key financial metrics pre and post-AI implementation.
🌐 Why This Matters: This research is not just academic; it's a crucial exploration into the economic effectiveness of AI technologies in business. By evaluating AI's ROI, you will add valuable insights to the discourse on strategic technology investments and their role in shaping future business models.
📚 Are You Ready to Dive Deep into AI’s Financial Impact? If the intersection of AI, business strategy, and financial analysis excites you, this master thesis is your launchpad. Embark on this journey with us to uncover the real value of AI investments in the business world! 🚀
🦾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 main goal is to conduct a thorough empirical study on the ROI of AI in business. This research will establish you as a knowledgeable scholar in the field, merging theory with practical financial analysis, and enhancing understanding of AI's economic impact on businesses.
📚 Further Reading
Further readings in the field:
- Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlström, P., ... & Trench, M. (2018). Skill shift: Automation and the future of the workforce. McKinsey Global Institute.
- Chui, M., Manyika, J., & Miremadi, M. (2016). Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly, 2016(3), 58-69.
- Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
- Huang, M. H., & Rust, R. T. (2020). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 48(1), 9-25.
- Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15-25.
- Ransbotham, S., Gerbert, P., Reeves, M., Kiron, D., & Spira, M. (2018). Artificial intelligence in business gets real: Pioneering companies aim for AI at scale. MIT Sloan Management Review.
- Susskind, R., & Susskind, D. (2015). The future of the professions: How technology will transform the work of human experts. Oxford University Press.
- Taddy, M. (2019). Business data science: Combining machine learning and economics to optimize, automate, and accelerate business decisions. McGraw-Hill Education.
📝 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