Enrolment options

TU-E1040 - Generative AI and Strategy D, Lecture, 4.9.2024-22.10.2024

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):

tero.i.ojanpera@aalto.fi


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.

  • applies in this implementation

    Week 1

    L1: Course basics and practicalities and Introduction to how Gen AI's impact in reshaping Industry
    L2: Introduction to Generative AI

    Week 2

    L1: Using Generative AI in Strategy Creation

    L2: Prompting Exercise

    Week 3

    L1: Generative AI for Product and Service Innovation

    • Exploring how generative AI can enhance or create new products and services, including industry examples.
    L2: AI in Business Processes
    • How AI streamlines business processes, with examples in logistics, customer service, and operations.

    Week 4

    Topic: Creating Competitive Advantage with Generative AI

    • Explore strategic frameworks to strengthen competitive positioning with GenAI.


    Week 5

    L1: Generative AI and Data Usage

    • Exploring legal and strategic considerations around data used for training Gen AI
    L2: Ethical Implications of Generative AI
    • Discussing ethical dilemmas, bias, and fairness in Gen AI applications.

    Week 6

    L1: Generative AI’s Impact on Society

    • How Gen AI is reshaping societal domains such as employment, education, and privacy

    L2: AI and Geopolitics
    • The role of AI in shaping global power dynamics and international relations.

    Case Study

    Timeline: Period I & II
    Prepare a 10-page Gen AI-based strategy for your selected company. You will also work on the case study during lectures.


Assessment Methods and Criteria

  • valid for whole curriculum period:

    Lecture presence, weekly assignments and strategy case study.

  • applies in this implementation

    Grading 1-5, maximum 100 points = 5
    - 3p: Lecture presence (6 lectures, 0,5p each, 1,5p minimum required)

    - 7p: MyCourses pre-lecture quiz (1-2p each quiz) 
    - Assignments for each week module
    ■ M1: 10p
    ■ M2: 10p
    ■ M3: 10p
    ■ M4: 10p
    ■ M5: 10p
    ■ M6: 10p
    60 points
    Strategy case study 30 points

    For home assingments 

    • Cover topics in the lecture and give examples
    • Provide new insights and creativity
    • Provide structure and clarity

Workload

  • valid for whole curriculum period:

    Lectures and independent work.

  • applies in this implementation

    Each week's module includes pre-readings, quizzes, lectures, and an assignment that typically applies the concepts to a strategy case study of the selected company.

    Modules M1-M5: Total 50 hours (5 modules, 10 hours each)

    • Pre-readings: 4 hours
    • Lectures: 2 hours
    • Assignments: 4 hours

    After completing all lectures, students will work on a strategy case study (40 hours). Additionally, a reflection component will add 30% more time to the preceding work.

    Total work laod : 135h (5 cr)



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


Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof

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