This course, Utilizing AI for Business, supports the Mission Statement of Nagoya University of Commerce & Business Business School by fostering leaders who can evaluate and strategically apply AI to business challenges. By integrating the craftsmanship spirit of Kaizen, continuously seeking innovative solutions, students will develop frontier leadership skills that enable them to responsibly design AI strategies that contribute to the development of business and society, while connecting the new era of Asia with the world.

By studying this course, students will deepen their ability to critically evaluate how AI can empower business and conclude how it should be implemented in practice. The purpose is not to provide technical AI literacy, but to train students to,

- Judge whether AI is the right solution for a business challenge,

- Redesign organizations to support AI adoption,

- Build governance structures to mitigate internal politics,

- Create AI strategies and practical action plans.

Students are encouraged to adopt a Kaizen mindset of craftsmanship, approaching AI not as a one-off tool but as part of an ongoing process of searching for more effective and innovative solutions.

By the end of this course, students will be able to,

- Knowledge and Understanding: Explain the strategic significance of AI and evaluate when AI can empower business,

- Specialized Skills: Conclude where and how AI can be applied, and design organizational and governance structures to support adoption,

- General Abilities: Formulate comprehensive AI strategies and translate them into actionable plans,

- Attitudes: Cultivate a forward-looking and innovative mindset, reflecting the Kaizen spirit of continuously seeking better solutions.

*本学の教育ミッションを具現化する形で設定されています。

By completing this course, students will gain,

- The ability to critically assess whether AI is the right solution for business problems,

- Knowledge of organizational redesign and governance to support AI adoption,

- Skills to develop AI strategies that mitigate internal politics and foster ethical implementation,

- Practical experience in creating AI action plans that can be executed in organizations,

- The mindset of continuous innovation, rooted in Kaizen craftsmanship, for refining strategies and addressing evolving challenges.

教育手法 Teaching Method		% of Course Time
インプット型 Traditional		25 %
参加者中心型 Participant-Centered Learning	ケースメソッド Case Method	75 %
	フィールドメソッド Field Method	0 %
合計 Total		100 %

I. Prerequisites for the Course
To maximize your learning experience, students are expected to dedicate 2 to 4 hours of
preparation before each case. This includes:
1. Pre-Class Preparation:
- Read the assigned materials and references in advance.
- Be prepared for class discussions and questions that will arise during each session.
2. Post-Class Review:
- Read related cases to further deepen your understanding of the lecture content.
- Study the precedent cases covered in class by referring to the provided case materials.

Active engagement in pre-class readings and post-class review will enhance your
comprehension and contribute to meaningful class discussions.

II. Preparatory Report

Case to be used: The required cases for each day.
Assignment: Submit a one page summary of each cases, and a 2 page critical reasoning on your thoughts integrating the summary of the cases. Detailed instructions will be given before the class starts.
Submission Deadline: Before 9 am of the class day.
Submission Method: Submit via Google Classroom (within 5 A4 pages, Time New Roman Font 12, Double Space, PDF).

III. Final Report

Case to be used: All cases.
Assignment: Choose a company to do research and build an AI Strategy using the materials we have learned in Class. This may turn into a group project, based on the size of the class.
Submission Deadline: 11 pm on the final class day.
Submission Method: Submit via Google Classroom (within 20 A4 pages, Time New Roman Font 12, Double Space, PDF).

*成績は下記該当項目を基に決定されます。
*クラス貢献度合計はコールドコールと授業内での挙手発言の合算値です。

講師用内規準拠 Method of Assessment	Weights
コールドコール Cold Call	0 %
授業内での挙手発言 Class Contribution	70 %
クラス貢献度合計 Class Contribution Total	70 %
予習レポート Preparation Report	15 %
小テスト Quizzes / Tests	0 %
シミュレーション成績 Simulation	0 %
ケース試験 Case Exam	0 %
最終レポート Final Report	15 %
期末試験 Final Exam	0 %
参加者による相互評価 Peer Assessment	0 %
合計 Total	100 %

評価の留意事項　Notes on Evaluation Criteria

Students are expected to study the cases assigned for each day.
By university policy, active class participation is a fundamental component of this course, accounting for 70% of your final grade. In assessing class participation, emphasis will be placed on the quality of
contributions rather than mere frequency. Thoughtful engagement in discussions - demonstrating logical reasoning and deep insights - will be valued over simply sharing facts, paraphrasing, or summarizing previous points.

When contributing to discussions, students are expected to present well-structured arguments
with clear, articulate points. Superficial or vague responses will not be considered substantive
participation.

* Important: Failing to participate in discussions will result in a low participation grade.

Preparatory reports and the final report are graded based on effort and logical arguments.
These reports are not simple summaries of cases, and it is important to deliver your original thoughts and critical reasoning based on the case. Grading will be based on the strength of your original thoughts.

Turning in the assignment with poor English is fine. I emphasize that using AI to write your reports is strictly prohibited, which in case I judge that it is written by AI, the report will receive zero points.

• 配布資料

The following are additional resource books but not required for reading.

1) Iansiti, Marco, and Karim R. Lakhani. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Harvard Business Review Press, 2020.
2) Miller, Chris. Chip War: The Fight for the World’s Most Critical Technology. Scribner, 2022.

This course is first to be opened at NUCB Business School, and it is my first year teaching this course at NUCB Business School.

This course was previously opened for the first time in several countries by myself, at its prestigious top schools of each country.