Strategic Decision-Making with AI (MSB260)
In this course, we delve into the intersection of competitive strategy and artificial intelligence (AI), providing students with a comprehensive toolkit to navigate the complexities of today's business landscape. Students will learn how core concepts from strategic analytics and managerial economics can be applied to develop and determine strategies that allow them to grow a firm's profits within specific competitive contexts, with an added focus on AI. While AI may seem daunting, we have designed this course to be accessible, ensuring that students can confidently leverage these tools regardless of their technical background. By merging AI methodologies with traditional strategic principles, our goal is to empower students with the capability to make informed, data-driven decisions in a landscape where competitors are equally knowledgeable and consumers are highly informed. In today's fast-paced business environment, AI plays a crucial role in giving organizations a competitive edge. This course prepares students to be at the forefront of the AI revolution, equipping them with the skills and knowledge needed to leverage AI for strategic advantage and drive their organizations forward.
NB! This is an elective course and may be cancelled if fewer than 10 students are enrolled by January 6th for the spring semester.
Course description for study year 2024-2025. Please note that changes may occur.
Course code
MSB260
Version
1
Credits (ECTS)
10
Semester tution start
Spring
Number of semesters
1
Exam semester
Spring
Language of instruction
English
Content
The course covers a range of topics that blend classic competitive strategy with the latest AI applications, utilizing common software such as Excel and Python, including:
- Utilizing principles from strategic analytics and managerial economics to devise growth strategies and enhance profits, while also gaining an understanding of AI basics.
- Demand analysis, business forecasting, and industry analysis in the digital age.
- Competitor dynamics, positioning, and competitive advantage in an AI-driven world.
- Product differentiation, pricing strategies, and advertising optimization using AI insights.
- Strategic behavior, game theory, and quantitative methods for analyzing industry competitiveness.
Throughout the course, students will have the opportunity to analyze and solve real-world business problems, such as enhancing competitive positioning, optimizing product portfolios, and identifying strategic market opportunities, using AI tools.
Learning outcome
Knowledge: Upon completion of the course, students will have a solid understanding of:
- Strategic principles in competitive markets and industry analysis.
- Fundamental statistical concepts and data analysis methods.
- Core concepts of machine learning and deep learning.
- Application of AI tools in solving strategic business decisions.
Skills: Students will be able to:
- Utilize common software such as Excel and Python for strategic decision-making.
- Conduct market analysis and profit optimization.
- Develop and implement competitive strategies using AI insights.
- Optimize advertising and pricing tactics and budgets.
- Analyze competitive dynamics and industry competitiveness using AI tools.
This course utilizes cutting-edge AI software from Python, providing students with hands-on experience in applying AI tools to strategic business decisions. Additionally, students will work on a comprehensive hands-on project that simulates real-world strategic challenges faced by businesses today. AI methodologies can significantly enhance strategic decision-making by providing deeper insights, predicting future trends, and optimizing operations. In this course, students will learn how to integrate AI tools with traditional strategic principles to develop innovative solutions that address complex business challenges.
Required prerequisite knowledge
Exam
Term paper and school exam
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Term paper in groups | 45/100 | 1 Semesters | Letter grades | |
| School exam | 55/100 | 4 Hours | Letter grades | Valid calculator |
The final grade is based on a group project and a final individual exam. No re-sit. The term paper (45%): work in groups of 3-4 students. Due at the end of the term.Individual digital written exam (55%).