| 授業名 | Innovation by AI & Big Data |
|---|---|
| Course Title | Innovation by AI & Big Data |
| 担当教員 Instructor Name | Giulio Toscani |
| 授業形態 Class Type | 講義 Regular course |
| 授業形式 Class Format | On Campus |
| 単位 Credits | 2 |
| 言語 Language | EN |
| 科目区分 Course Category | 応用科目200系 / Applied |
| 学位 Degree | MSc in Management / Business Analytics & AI |
| 開講情報 Terms / Location | 2026 GSM Nagoya Fall |
| コード Couse Code | GLP262_G26N |
授業の概要 Course Overview
Mission Statementとの関係性 / Connection to our Mission Statement
This course is designed to empower both emerging and established leaders across industries with the knowledge and skills to drive innovation through Big Data and AI. Participants will discover how to harness these technologies to gain a competitive edge and forge deeper connections with customers. By adopting the principles of the "Disrupt" innovation methodology, they will not only analyze data and utilize technology but also integrate them into their organization's strategic vision. Ultimately, this course equips leaders to strategically leverage data and cutting-edge technologies, propelling their organizations toward sustainable success and growth.
授業の目的（意義） / Importance of this course
This course is instrumental because it will prepare leaders to harness the power to innovate before their competitors do. Participants will gain a deeper understanding of what “disrupt” is and will learn how to spot potential threats and opportunities in their own business.
学修到達目標 / Achievement Goal
By studying this course, students will be able to:
Understand the forces of disruption that could impact their business and see how to spot them early
Uncover a new approach for customer centricity to spot and shape new opportunities by applying the jobs to be done framework
Learn, through practical examples, how to leverage new business models and potential application for their companies
Get hands-on experience using the “disrupt” toolkit
Understand the forces of disruption that could impact their business and see how to spot them early
Uncover a new approach for customer centricity to spot and shape new opportunities by applying the jobs to be done framework
Learn, through practical examples, how to leverage new business models and potential application for their companies
Get hands-on experience using the “disrupt” toolkit
本授業の該当ラーニングゴール Learning Goals
*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。
LG1 Critical Thinking
LG4 Effective Communication
LG5 Executive Leadership (EMBA)
LG6 Innovative Leadership (MBA)
LG7 Global Perspective (GLP)
LG4 Effective Communication
LG5 Executive Leadership (EMBA)
LG6 Innovative Leadership (MBA)
LG7 Global Perspective (GLP)
受講後得られる具体的スキルや知識 Learning Outcomes
Understand the Role of Big Data and AI: Participants will develop a strategic grasp of how Big Data and AI can be leveraged using the Disrupt methodology to gain a decisive competitive advantage.
Explore Cutting-Edge Technologies: Through the Disrupt approach, participants will engage with the latest technological advancements, enabling them to identify and implement innovative tools that strengthen customer connections and business performance.
Enhance Customer Understanding: By applying the Disrupt methodology, learners will cultivate a deeper understanding of customer expectations, allowing them to design more tailored, impactful products and services.
Become Dynamic and Strategic Leaders: This course equips participants with the skills to move beyond conventional data analysis and technology adoption, positioning them as agile, forward-thinking leaders capable of driving transformational change in an evolving business landscape.
Explore Cutting-Edge Technologies: Through the Disrupt approach, participants will engage with the latest technological advancements, enabling them to identify and implement innovative tools that strengthen customer connections and business performance.
Enhance Customer Understanding: By applying the Disrupt methodology, learners will cultivate a deeper understanding of customer expectations, allowing them to design more tailored, impactful products and services.
Become Dynamic and Strategic Leaders: This course equips participants with the skills to move beyond conventional data analysis and technology adoption, positioning them as agile, forward-thinking leaders capable of driving transformational change in an evolving business landscape.
SDGsとの関連性 Relevance to Sustainable Development Goals
Goal 4 質の高い教育をみんなに（Quality Education）
教育手法 Teaching Method
| 教育手法 Teaching Method | % of Course Time | |
|---|---|---|
| インプット型 Traditional | 50 % | |
| 参加者中心型 Participant-Centered Learning | ケースメソッド Case Method | 30 % |
| フィールドメソッド Field Method | 20 % | 合計 Total | 100 % |
事前学修と事後学修の内容、レポート、課題に対するフィードバック方法 Pre- and Post-Course Learning, Report, Feedback methods
This “Innovation by Big Data & AI” course empowers leaders to leverage these technologies for competitive advantage. Using the "Disrupt" methodology, participants learn to identify disruptive forces, understand customers, and develop innovative business models. Hands-on case studies and workshops offer practical experience with the "Disrupt toolkit." Post-learning, students can understand disruption, apply customer-centric frameworks, leverage new models, and use the toolkit. Assessment includes class participation (75%) and a final report (25%) analyzing a chosen company and integrating course material. Feedback is provided in writing on the report.
授業スケジュール Course Schedule
第1日（Day1）
This session introduces the concept of “disrupt” and its transformative influence on industries worldwide. We will examine the fundamentals of Big Data AI, exploring how it is reshaping traditional business models and creating new avenues for innovation. Through this exploration, you will gain a deeper understanding of the potential of data-driven approaches to fuel innovation and learn about the key components that define a disruptive ecosystem.Disruptive Innovation Workshop Overview
The session sets the stage for understanding the interplay between disruptive innovation and emerging technologies, offering a practical framework to analyze and apply these principles in real-world scenarios.
Big Data and AI Technologies in Action
Real-world case studies will showcase how companies have leveraged Big Data and AI technologies to revolutionize their operations and secure competitive advantages. We will explore data-driven strategies and actionable techniques for identifying and capitalizing on disruptive opportunities.
Case Studies
●使用するケース
• Case 1• Case 2
• Case 3
第2日（Day2）
Unleashing the Power of AI for DisruptionIn this session, we explore the transformative role of AI as a catalyst for disruption, building on the foundation laid in the previous session. The focus will be on how advanced techniques like machine learning and deep learning enable groundbreaking applications that redefine industries and shift market dynamics. By exploring diverse case studies, you will see how AI-powered solutions are driving innovation and challenging established norms.
Overcoming Challenges in Data-Driven Disruption
AI-driven disruption comes with its own set of challenges. In this segment, we will address key obstacles such as data privacy concerns, ethical dilemmas, and regulatory complexities. The discussion will highlight strategies for mitigating these risks while fostering responsible innovation. By examining best practices, you will learn how to navigate the evolving landscape of disruptive technologies and ensure ethical and sustainable growth.
Adopting a User-Centric Approach
To maximize the potential of AI in disruption, it is essential to focus on unmet user needs. You will learn techniques for identifying these needs, prototyping innovative solutions, and designing impactful, user-centric experiences that resonate in the digital era.
●使用するケース
Case Studies in AI-Driven Disruption• Case 4
• Case 5
• Case 6
This session equips you with the insights and tools to harness AI’s disruptive power while addressing the challenges and opportunities of this transformative era.
第3日（Day3）
Embracing “Disrupt”: Strategies for SuccessIn this session, we will analyse the strategies organizations can use to embrace disruption and turn it into a competitive advantage. The focus will be on fostering organizational agility, attracting and developing the right talent, and driving a cultural transformation that supports innovation and adaptability. Through the exploration of real-world cases, we will uncover how companies across diverse sectors have navigated disruption caused by Big Data and AI.
●使用するケース
Case Studies in AI-Driven Disruption• Case 7
• Case 8
第4日（Day4）
Through the exploration of Meetup case, we will uncover how companies across diverse sectors have navigated disruption caused by Big Data and AI. Each case highlights distinct approaches to leveraging data-driven insights and technological advancements to reimagine business models, engage customers, and create value.By the end of this session, you will gain actionable strategies and a practical roadmap for using data-driven innovation to transform your organization and lead in disruptive environments. You will be equipped to proactively adapt to change, foster a culture of experimentation, and seize opportunities to shape the future of your industry.
●使用するケース
Case Highlights:• Case 9
成績評価方法 Evaluation Criteria
*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。
*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 | 75 % |
| クラス貢献度合計 Class Contribution Total | 75 % |
| 予習レポート Preparation Report | 0 % |
| 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 | 25 % |
| 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
教科書 Textbook
- Toscani, G.「Augmented: prAIority to Enhance Human Judgment through Data and AI.」Routledge（2025）
参考文献・資料 Additional Readings and Resource
How Incumbents Survive and Thrive By: Julian Birkinshaw
Persuade Your Company to Change Before It's Too Late By: Pontus M.A. Siren; Scott D. Anthony; Utsav Bhatt
Adapting to Digital Disruption By: Julian Birkinshaw; Thomas W. Malnight; Ivy Buche; Pontus M.A. Siren; Scott D. Anthony; Utsav Bhatt; Jonathan Knee; Alison Beard
Can Big Tech Be Disrupted? By: Jonathan Knee; Alison Beard
Persuade Your Company to Change Before It's Too Late By: Pontus M.A. Siren; Scott D. Anthony; Utsav Bhatt
Adapting to Digital Disruption By: Julian Birkinshaw; Thomas W. Malnight; Ivy Buche; Pontus M.A. Siren; Scott D. Anthony; Utsav Bhatt; Jonathan Knee; Alison Beard
Can Big Tech Be Disrupted? By: Jonathan Knee; Alison Beard
授業調査に対するコメント Comment on Course Evaluation
A student’s final grade in this course will be based on the following weighting:
25% Class Participation
75% Individual final project and cases
Assessment reflects the quality of a student’s active participation in class discussions. Much of a manager’s success depends on communication; therefore, effective oral communication will constitute the student’s grade. Written work should be clear, logical, grammatically correct, spell-checked, persuasive, supported by examples, and backed up by citations for any data, ideas or other content used. It should represent the student’s best effort. To do well on the writing reports, you will need to incorporate and apply the course readings.
A note on Class participation:
Grading class participation is necessarily subjective. However, I try to make it as “objective as possible”. Some of the criteria for evaluating effective class participation include:
1 Is the participant prepared? Do comments show evidence of analysis of the case? Do comments add to our understanding of the situation? Does the participant go beyond simple repetition of case facts without analysis and conclusions? Do comments show an understanding of theories, concepts, and analytical devices presented in class lectures or reading materials?
2 Is the participant a good listener? Are the points made relevant to the discussion? Are they linked to the comments of others? Is the participant willing to interact with other class members?
3 Is the participant an effective communicator? Are concepts presented in a concise and convincing way?
The final course grade for a student will be determined based on the following weight distribution, incorporating three evaluation objective criteria:
Class Participation: 75%
Objective Criteria 1: Engagement Level
This evaluation measures the extent of a student's active engagement in class discussions. Recognizing the crucial role of communication in managerial success, a substantial portion of the student's grade is attributed to effective oral communication. Written assignments are expected to demonstrate clarity, logical coherence, grammatical accuracy, spell-check verification, persuasiveness, supported by examples, and substantiated by citations for data, ideas, or other content. It should embody the student's utmost effort, incorporating and applying insights from course readings.
Class Participation Guidelines:
Participation entails attending all class sessions, completing assigned readings, and actively participating in exercises and discussions. Full attendance throughout on-campus sessions is mandatory, and tardiness or early departure may lead to removal from the class. Grading criteria for effective class participation encompass preparedness, substantive comments, relevance to discussions, peer interaction, and effective communication.
Individual Final Project: 25%
Objective Criteria 2: Analytical Depth
Serving as the culmination of course learnings, the Individual Final Project necessitates students to leverage readings and discussions to present a thorough analysis.
Project Guidelines:
To prevent inappropriate use of GPT and fulfill the course criteria, students must structure their assignments according to the six specified sections provided below. This entails creating a Word document (with a minimum of 2,000 words) that examines and assesses the significant impact of the course subject on the contemporary business landscape. Failure to adhere to these criteria will result in an automatic course failure.
Project Sections:
First of all, think of a company you want to analyze (if already existing, what you want to innovate in their current offering).
1. Introduction: Briefly outline the significance of the course subject in the contemporary business environment using the real company you choose as an example. Clearly articulate how the real company chosen fits with this course, providing this section with at least four course slide screenshots to explain the fit.
2. Selection: Examine how the course concepts helped you select the real company chosen explaining the relationship of your idea with DEEPER NEED, VALUE CREATION AND CAPTURING, PAAS (PRODUCT AS A SERVICE), ANCHORING vs. OBSERVING/INTERVIEWING USERS, AND THE ART OF ASKING QUESTIONS and describe how this process occurred, providing this section with at least five course slide screenshots.
3. The matrix of disruption: Identify the variables (minimum five VARIABLES) you have identified for innovating the company and discuss in detail how you have expanded, reduced, flipped (opposite) and denied by building the matrix of opportunitie (Show the matrix and more slides of how you applied it).
5. Conclusions and Learning Reflections: Summarize key findings and insights, providing concluding remarks on the overall impact of the course subject on your learning, supported by a specific example and by at least three course slide screenshots.
END WITH THE PHRASE
A [label] that allows [users] to [benefit] by [method]
6. References: Ensure proper citation using a recognized citation style (e.g., APA, MLA, Chicago).
Submission Guidelines:
The assessment of the assignment will consider the sections outlined above, each assessing: the clarity of explanation, writing style, formatting, quality and quantity of visual content, and the feasibility of the project.
Do not forget to put your name both on the file name and at the heading of the document
Contextualization Requirement:
Objective Criteria 3: Integration of Course Material
Note: Successful completion of the assignment hinges on contextualization, serving as the primary method to deter improper utilization of ChatGPT and meet course requirements. This entails integrating course-specific components such as personal notes, referenced quotes from lectures or peers, instances from course materials, and visual aids from presentation slides. Failure to contextualize your assignment within the course framework, as per the six-sections criteria, will lead to a failing grade. Previous unsuccessful assignments include those lacking the prescribed six-section structure and those discussing your project without integrating course material.
25% Class Participation
75% Individual final project and cases
Assessment reflects the quality of a student’s active participation in class discussions. Much of a manager’s success depends on communication; therefore, effective oral communication will constitute the student’s grade. Written work should be clear, logical, grammatically correct, spell-checked, persuasive, supported by examples, and backed up by citations for any data, ideas or other content used. It should represent the student’s best effort. To do well on the writing reports, you will need to incorporate and apply the course readings.
A note on Class participation:
Grading class participation is necessarily subjective. However, I try to make it as “objective as possible”. Some of the criteria for evaluating effective class participation include:
1 Is the participant prepared? Do comments show evidence of analysis of the case? Do comments add to our understanding of the situation? Does the participant go beyond simple repetition of case facts without analysis and conclusions? Do comments show an understanding of theories, concepts, and analytical devices presented in class lectures or reading materials?
2 Is the participant a good listener? Are the points made relevant to the discussion? Are they linked to the comments of others? Is the participant willing to interact with other class members?
3 Is the participant an effective communicator? Are concepts presented in a concise and convincing way?
The final course grade for a student will be determined based on the following weight distribution, incorporating three evaluation objective criteria:
Class Participation: 75%
Objective Criteria 1: Engagement Level
This evaluation measures the extent of a student's active engagement in class discussions. Recognizing the crucial role of communication in managerial success, a substantial portion of the student's grade is attributed to effective oral communication. Written assignments are expected to demonstrate clarity, logical coherence, grammatical accuracy, spell-check verification, persuasiveness, supported by examples, and substantiated by citations for data, ideas, or other content. It should embody the student's utmost effort, incorporating and applying insights from course readings.
Class Participation Guidelines:
Participation entails attending all class sessions, completing assigned readings, and actively participating in exercises and discussions. Full attendance throughout on-campus sessions is mandatory, and tardiness or early departure may lead to removal from the class. Grading criteria for effective class participation encompass preparedness, substantive comments, relevance to discussions, peer interaction, and effective communication.
Individual Final Project: 25%
Objective Criteria 2: Analytical Depth
Serving as the culmination of course learnings, the Individual Final Project necessitates students to leverage readings and discussions to present a thorough analysis.
Project Guidelines:
To prevent inappropriate use of GPT and fulfill the course criteria, students must structure their assignments according to the six specified sections provided below. This entails creating a Word document (with a minimum of 2,000 words) that examines and assesses the significant impact of the course subject on the contemporary business landscape. Failure to adhere to these criteria will result in an automatic course failure.
Project Sections:
First of all, think of a company you want to analyze (if already existing, what you want to innovate in their current offering).
1. Introduction: Briefly outline the significance of the course subject in the contemporary business environment using the real company you choose as an example. Clearly articulate how the real company chosen fits with this course, providing this section with at least four course slide screenshots to explain the fit.
2. Selection: Examine how the course concepts helped you select the real company chosen explaining the relationship of your idea with DEEPER NEED, VALUE CREATION AND CAPTURING, PAAS (PRODUCT AS A SERVICE), ANCHORING vs. OBSERVING/INTERVIEWING USERS, AND THE ART OF ASKING QUESTIONS and describe how this process occurred, providing this section with at least five course slide screenshots.
3. The matrix of disruption: Identify the variables (minimum five VARIABLES) you have identified for innovating the company and discuss in detail how you have expanded, reduced, flipped (opposite) and denied by building the matrix of opportunitie (Show the matrix and more slides of how you applied it).
5. Conclusions and Learning Reflections: Summarize key findings and insights, providing concluding remarks on the overall impact of the course subject on your learning, supported by a specific example and by at least three course slide screenshots.
END WITH THE PHRASE
A [label] that allows [users] to [benefit] by [method]
6. References: Ensure proper citation using a recognized citation style (e.g., APA, MLA, Chicago).
Submission Guidelines:
The assessment of the assignment will consider the sections outlined above, each assessing: the clarity of explanation, writing style, formatting, quality and quantity of visual content, and the feasibility of the project.
Do not forget to put your name both on the file name and at the heading of the document
Contextualization Requirement:
Objective Criteria 3: Integration of Course Material
Note: Successful completion of the assignment hinges on contextualization, serving as the primary method to deter improper utilization of ChatGPT and meet course requirements. This entails integrating course-specific components such as personal notes, referenced quotes from lectures or peers, instances from course materials, and visual aids from presentation slides. Failure to contextualize your assignment within the course framework, as per the six-sections criteria, will lead to a failing grade. Previous unsuccessful assignments include those lacking the prescribed six-section structure and those discussing your project without integrating course material.
担当教員のプロフィール About the Instructor
EDUCATION: Artificial Intelligence: Implications for Business Strategy (2018.) MIT, Massachusetts Institute of Technology, Sloan & MIT CSAIL. Cambridge, USA
PhD in Management (2018).KTH, Royal Institute of Technology. Stockholm, Sweden.
BSc and MSc in Chemical Engineering (1999). Italy/UCL London, UK
（実務経験 Work experience）
Professor and Advisor
• ESADE Business and Law School, Barcelona, Spain. Adjunct Professor
Law School degree: Digital Technologies Impact
MIBA (Master in Business Analytics) & MBA: Human + Machine strategy
Executive education: Remote teams; Digital Entrepreneurship; Leadership in AI.
• Pacifico Business School, Lima, Perú. Adjunct Professor
• University of Bath, Bath, UK. Visiting Professor. MBA Programme: Contemporary issues at the time of Big Data/ Artificial Intelligence
• NUCB Nagoya University of Commerce and Business, Nagoya, Japan. Visiting Professor. MBA programme: Disruption by Big Data|Artificial Intelligence
• Ranepa Business School, Moscow, Russia. Visiting Professor. Global MBA: Digital Entrepreneurship
• Politecnico, Milan, Italy. Visiting Professor. Master in Strategic Design: Design Thinking in AI
• Navozyme, Singapore. Advisory Board.
• Programme Director Universitas Telefónica. Barcelona, Spain.
Direction and Teaching of the Programmes for Telefonica Global Executives
Publications
Sponsees: the silent side of sponsorship research (Arts Sponsorship)
G Toscani, G Prendergast
Marketing Intelligence & Planning 36 (3), 396-408 22
2018
Arts Sponsorship Versus Sports Sponsorship: Which Is Better for Marketing Strategy?
G Toscani, G Prendergast
Journal of Nonprofit & Public Sector Marketing 19
2018
Behaviour of different treated and untreated stones exposed to salt crystallization test
R Quaresima, G Toscani
5th:; International symposium, Conservation of monuments in the … 4
2002
UNDERSTANDING THE SPONSEE'S EXPERIENCE: AN ASSESSMENT OF THE SPONSOR-SPONSEE RELATIONSHIP
G Toscani
KTH Royal Institute of Technology 2
2018
Political Art: An Investigation of the Jacob Zuma Spear Painting
BE Stiehler, G Toscani
Ideas in Marketing: Finding the New and Polishing the Old, 516-525 2
2015
Leading successful AI projects in three words: group, relevant, and empathetic
G Toscani
Do Better by ESADE 2022
How Artificial Intelligence (AI) experts’ skills relate to AI solution outputs
G Toscani
Under Review 2023
The effects of the COVID-19 pandemic for AI practitioners: the decrease in tacit knowledge sharing
G Toscani
Journal of Knowledge Management 2022
The role of reciprocity and reputation in service relationships with arts organisations (Arts Sponsorship)
G Toscani, G Prendergast
Journal of services marketing 2021
CONTRASTING SPORTS SPONSORSHIP AND ARTS SPONSORSHIP
G Toscani, G Prendergast
7th World Business Ethics Forum 2018
ARTS SPONSORSHIP VERSUS SPORTS SPONSORSHIP: WHICH IS BETTER FOR MARKETING STRATEGY?
G Toscani, G Prendergast
The sponsor-sponsee relationship through the lens of the sponsee
G Toscani, G Prendergast
Politics and art: An exploratory study investigating the hype caused by the Jacob Zuma Spear painting
G Toscani, BE Stiehler
Appendix (E): Emerged Working Papers
G Toscani, G Prendergast
Refereed Articles
- (2025) Integrating minds: adaptive knowledge sharing strategies for ML team synergy. Cognition, Technology & Work
- (2025) EXAPTATION AS A STRATEGIC MECHANISM IN PUBLIC R&D: CHALLENGES AND SOLUTIONS AT THE BARCELONA SUPERCOMPUTING CENTER. The Journal of Supercomputing
- (2025) El arte de la aumentación: integrando IA, datos y juicio humano en la era digital. Harvard Deusto Business review (356):
- (2025) From code to context: the impact of organizational problem framing on machine learning success. Journal of Decision Systems 34(1):
- (2025) El poder del trinomio formado por el ser humano, la IA y el ‘big data’. Harvard Deusto Business review (351):