📌 Key facts
🔹 Starting date: Start anytime. Applications open now!
🔹 How to apply: Send an email including your CV and grade report, and research interest (Details at the end of this page).
- 📌 Key facts
- 💡 Background
- 🧠 Thesis Proposal
- 🦾Who We Are
- 🎓 Expectations
- 📄 Requirements to any Work
- 📬 How to apply
💡 Background
Our AI Strategy Research Cluster at TUM x BCG is on a mission to uncover how AI truly creates value beyond the hype. While many organisations have launched GenAI initiatives, few can demonstrate measurable top- or bottom-line impact. We believe that one potential missing link lies in how humans interact with AI: How they trust it, adapt to it, and integrate it into workflows and decision-making. From cognitive biases in Human-AI interaction to cross-level productivity effects and organisational learning loops, we investigate what really drives or hinders AI success. Our work blends behavioural science, organisational theory, and rigorous empirical methods to tackle one of the most pressing questions in today's digital transformation: What conditions must be met for AI to deliver on its promise? Join us to push the frontier of AI research and help shape the future of human-centred AI adoption in real-world organisations.
🧠 Thesis Proposal
- Designing an Agentic AI for Employee Feedback (Design Science Approach) This thesis will use a design science methodology to create and evaluate a conversational “belief audit” AI agent that employees trust and readily engage with. By leveraging HCI principles like the Computers as Social Actors paradigm and the Technology Acceptance Model, the study will prototype different agent persona designs (e.g. varying tone, friendliness, anonymity features) and test their impact on employee participation and honesty in feedback sessions. The practical payoff is a set of design guidelines platform to maximize user adoption and candid input, ensuring richer bottom-up signals for strategic decision-making. Database: Experimental design, collection of real company data (TBD)
- Strategic Sensemaking via AI-Mediated Weak Signal Detection This research explores how deploying an agentic AI in organizations can enhance strategic sensemaking and double-loop learning. In a field quasi-experiment, the AI will conduct “belief audits” with employees to surface weak signals (early signs of issues or ideas) and aggregate diverse perspectives for management. The study will examine whether teams using the AI-generated insights (vs. those that don’t) achieve deeper collective understanding and adapt their strategies more effectively (consistent with open strategy principles of inclusive planning). Findings will contribute to academic debates on organizational learning by showing if AI feedback loops help leaders challenge assumptions and improve strategic alignment in practice. Database: Experimental design, collection of real company data (TBD)
- Nudging Employee Voice through AI Agents (Behavioral Economics Experiment) This thesis applies behavioral economics to encourage employees to speak up and share honest feedback with AI-based agents. Many employees stay silent about problems due to fear or futility, so psychological safety is critical. The research will design gentle “nudges” in a conversational agent prototype– and test their effect on participation rates and candor in a real company setting (e.g. comparing teams with vs. without these nudges). By measuring increases in feedback quantity and quality, the study offers practical strategies to overcome organizational silence, helping Agentic AI applications to foster a more open, trustful feedback culture. Database: Experimental design, collection of real company data (TBD)
- Persuasive Agentic AI: Evaluating the Influence of Conversational Agents on Shaping Human Preferences and Decision-Making Recent advances in Agentic AI have enabled autonomous conversational systems capable not only of collecting information but also of subtly shaping human opinions and decisions. This thesis explores the design and behavioral impact of a persuasive AI agent using a field experiment, where children interact with a “Santa Claus” conversational agent to discuss their wish lists. The agent, in certain versions (A/B/C version), will nudge or persuade users to reconsider specific choices - encouraging reflection or prosocial alternatives (e.g., “Are there other wishes that might make you or others happier?”). After each conversation, parents will receive a short evaluation to measure the perceived change in the child’s expressed preferences and emotional response, allowing an assessment of AI persuasion efficacy and ethical boundaries. Database: Experimental design, we will activate and audit around 5-10k calls (TBD)
…. call for application, propose your research question relevant to a Agentic AI.
🦾Who We Are
We are a research collaboration between the Technical University of Munich (TUM) and the Boston Consulting Group (BCG), focused on exploring the business value of Artificial Intelligence (AI), particularly Generative AI. Combining academic depth with industry relevance, we investigate how AI creates measurable impact across organizations spanning people, processes, platforms, and policies. Our work is grounded in real-world implementations and aims to produce actionable insights for both scholarly and managerial audiences. 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
🎓 Expectations
- Applicants should have the desire to co-author a publication in an academic journal
- Strong academic track record is a pre-requirement, the average TUM grade must be <1.6
- Applicants should have interest in hands-on field research
- Reliable, structured, precise and self-driven working - pragmatic solution oriented
- Applicants should be digital natives, ability to code is a plus, but not a requirement
- Applicants need motivation, optimism, and should write their thesis with fun
📄 Requirements to any 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:
- Infograph - visually represent some of your work (find examples here)
- Slide Deck - Summarise your research and possibly present it
- Optional: Medium Article - let people outside the university know about your research and start your personal brand
Please note that these deliverables are not officially required.
📬 How to apply
📌 Send us a brief application including:
✅ Your CV
✅ Your Transcript of Records/Grade Report(Transcript of Records)
✅ Your preferred starting date & your research interest/motivation
✅ Your motivation via mail, don’t use GPT to generate your application
📩 E-Mail an: thilo.tamme@tum.de or tamme.thilo@bcg.com // Thilo Tamme Get in touch today, before others may take your thesis spot….! 🚀