Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

The students will during the course learn to 1) Understand, apply, analyze, evaluate, and create a strategy based on generative AI understanding its role in shaping business models and competitive advantages across various industries. 2) Apply generative AI tools and techniques in strategy creation including analyzing trends, creating scenarios, analyzing internal capabilities, assessing market opportunities and ‘right to win’, and creating an execution roadmap.

Credits: 5

Schedule: 04.09.2024 - 22.10.2024

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Tero Ojanperä

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    This course provides students with the skills necessary to develop and implement strategies based on generative AI technologies, such as large language models. It explores how generative AI shapes technology, workflows, and business models across various industries, and how it can be integrated into the strategic planning of a firm. Students will learn how strategies based on generative AI can fundamentally alter business operations and value creation and also about the societal and geopolitical impacts of generative AI, emphasizing its role in both business performance and broader societal contexts. Furthermore, students will learn how to use generative AI tools such as ChatGPT to create strategies.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    Lecture presence, weekly assignments and strategy case study.

Workload
  • valid for whole curriculum period:

    Lectures and independent work.

DETAILS

Study Material
  • valid for whole curriculum period:

    Academic articles, videos and other readings (see Syllabus),

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    8 Decent Work and Economic Growth

    9 Industry, Innovation and Infrastructure

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching language: English
    Teaching period:
    2024-2025 Autumn I
    2025-2026 Autumn I

    Enrollment: The number of students is limited. Students are admitted to the course in the following order: 1) Industrial Engineering and Management MSc students of Strategy Major, 2) Industrial Engineering and Management MSc students of other majors, 3) Other students