Syllabus

Title
2628 Elective - AI-Driven Decision Making
Instructors
Christian Schumacher, Ph.D.
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/05/25 to 09/16/25
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Tuesday 10/07/25 10:00 AM - 02:30 PM D5.1.004
Tuesday 10/14/25 02:00 PM - 06:30 PM Online-Einheit
Thursday 10/16/25 02:00 PM - 06:30 PM D5.1.004
Tuesday 10/21/25 02:00 PM - 06:30 PM D5.1.004
Thursday 10/23/25 10:00 AM - 02:30 PM D5.1.004
Contents

Strategic decisions determine a firm’s long-run performance—but they are notoriously hard: high stakes, pervasive uncertainty, slow and noisy feedback, and limited managerial bandwidth. Until recently these calls rested solely on human intuition and expertise. Rapid advances in artificial intelligence are reshaping that landscape, offering powerful, data-rich complements—provided leaders know how to deploy them.

This course equips candidates with the mind-sets and toolkits needed to fuse human judgment with state-of-the-art AI. Working hands-on with cutting-edge tools and real-world business scenarios, we will sharpen strategic decision-making.

Core Themes

  1. Strategic Decision-Making Fundamentals & Biases
    Frameworks for high-impact choices and the cognitive traps that derail them.

  2. AI as a Debiasing Coach
    Conversational agents that surface hidden assumptions, enable more rational negotiation, and institutionalize a “devil’s-advocate” discipline.

  3. AI-Augmented Data Interpretation
    Generative and predictive models that extract insight from complex, messy datasets—without outsourcing judgment.

  4. AI-Powered Scenario Generation
    Scaling foresight by generating, ranking, and stress-testing alternative futures to fortify strategic resilience.

Learning outcomes
  • Diagnose complex strategic challenges and the biases that undermine sound judgment.

  • Integrate AI capabilities with managerial intuition to enhance decision quality.

  • Translate data-driven insights into clear, action-oriented strategic options.

Attendance requirements

Students must attend at least 80 % of scheduled contact hours. Attendance in the final session is compulsory because the individual exam takes place then. 

Teaching/learning method(s)

Lectures, AI tools, Scientific Papers, Recent AI News, and more. 

Assessment

60 % Continuous assessment: individual & group deliverables plus active participation.

40 % Final individual case-based exam held in the last session

Readings

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Last edited: 2025-06-16



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