This course aims to provide students with the knowledge and skills necessary to critically analyze business models related to new information and communication technologies. In addition to understanding the implementation of emerging technologies, the objective is to develop the ability to apply them to innovate and improve business management, identifying the opportunities offered by the digital economy and assessing the strengths and weaknesses of various business models.

The course, which is multidisciplinary in nature, is based on the latest research on business management frameworks, with a focus on the integration of emerging technologies. It will critically analyze not only the opportunities but also the limitations, risks, and distortions that artificial intelligence (AI) may generate in the present and future.

The course aims to provide students with a comprehensive understanding of the phenomenon of new technologies, highlighting how they influence the economy, governance, and management. The course will delve into topics related to innovation, artificial intelligence, the evolution of business models, and the transformation of marketing and corporate communication, with particular attention to the shift from linear to circular management and the role of network technologies within the business ecosystem.

1. Why new technologies require Economy, Governance, and Management
- Origins and development of Artificial Intelligence (AI)
- Data on AI usage in Italy
- The value of AI
- The risks of AI

2. Innovation and Artificial and Augmented Intelligences: Evolutionary Reflections
- The AI Factory
- General approaches to machine learning
- Experimentation and A/B testing
- The AI production process
- The actors in the AI production and consumption process

3. Entrepreneurship and Artificial Intelligence
- Examples of AI: Chatbots
- Large Language Models (LLMs)
- Entrepreneurial evolution and AI
- Biases and resistance towards AI
- The Metaverse

4.The innovation of business models with and for emerging technologies
- The Business Model Canvas
- The adoption of AI in the business model
- Examples of Business Model Canvas

5. From business management to ecosystem management: the role of network technologies
- Limitations of AI in business management
- Applications and benefits of AI in management
- AI as an innovative ecosystem
- The Smart Society

6. From linear to circular management: network technologies reshaping the value chain
- Linear management vs circular management
- AI and circular management
- Limitations of the Circular Economy
- Areas where AI can support the Circular Economy
- Business model, AI, and circularity

7. The evolution of marketing with emerging technologies
- AI and marketing
- Advantages of applying AI in marketing
- The phases of Artificial Intelligence Marketing
- Examples of AI applications in marketing

8. The evolution of business communication with emerging technologies
- AI-Mediated Communication
- Main uses of AI for communication
- Corporate communication
- The role of AI in corporate communication

9. Knowledge management and AI
- What is Knowledge Management (KM)
- KM and digital technologies
- KM between creativity and rationality

No prerequisites are required in the study program's regulations.

At the end of the course, the student will acquire:

Knowledge and understanding

Recognize emerging technologies;
Identify the changes in business management caused by emerging technologies;
Identify new business models, including those based on emerging technologies;
Identify and recognize techniques for analyzing new business models.

Applied knowledge and understanding

Analyze and manage the changes in business management due to emerging technologies;
Analyze and define the potential of emerging technologies for one’s own business;
Analyze and manage the implementation phases of new business models;
Formulate innovative strategic choices that align with environmental and business conditions.

Independent judgment

The student will develop independent judgment in evaluating and interpreting the opportunities offered by emerging technologies for businesses and their ability to generate value, as well as the strategies to enhance innovation and express critical considerations.
Additionally, the student will be able to express analytical and synthetic evaluations on the key aspects of the subject and make interdisciplinary connections.

Communication skills

The student will acquire the terminology, tools, and skills to communicate the theoretical and applied aspects of the course in both written and oral forms.
The student will be able to understand problems, provide ideas and solutions related to business management that implements emerging technologies.
Moreover, the student will be able to communicate effectively to both expert and non-expert audiences using graphic and formal languages.

Learning skills

The student will acquire the ability to learn autonomously and self-assess their preparation, enabling them to enter the workforce or continue their studies with a good level of independence.

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it

During the course, seminars will be organized with scholars, industry professionals, as well as company CEOs.

Teaching

The course includes the use of various teaching methods:

- Face-to-face lectures
- Projection of slides and videos;
- Testimonials from entrepreneurs and industry experts;
- Classroom discussions.

Innovative teaching methods

• Consumption of videos and multimedia content;

• Individual or group exercises;

• In-depth studies that students will conduct using the materials uploaded to the university's Moodle platform.

Course books

Pironti, M. (2022). Intelligenze artificiali e aumentate: Elementi di economia e management. EGEA spa.

All chapters (1, 2, 3, 4, 5, 6, 7, 8, 9) except for chapter 10 (Finance and AI).

In addition to the textbook, it is recommended to deepen the course content with the course slides.

Note: Foreign students who are not comfortable studying the textbook in Italian will have the opportunity to explore the course topics through the relevant international scientific literature referenced in the book's notes.

Assessment

The expected learning outcomes will be assessed through a written exam divided into two parts:

First structured part: 20 multiple-choice questions (each question is worth 1 point for a total of 20 points). The goal of this section is to evaluate the mastery of declarative knowledge and the ability to understand concepts and representations.

Second unstructured part: 2 open-ended questions (each question is worth a maximum of 6 points). The evaluation criteria are: the level of mastery of the knowledge, the adequacy and articulation of the response, and the accuracy of the language used, along with the use of explanatory examples where required.

The maximum achievable score is 32 points, equivalent to a score of 30 with honors. The exam is passed if a minimum score of 18 is obtained.

The time allotted to answer the proposed questions is 45 minutes, and the exam score is expressed in thirtieths.

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

Teaching

Non-attending students are invited to consult the teaching materials uploaded on Moodle (slides discussed during lectures, seminars, etc.), through which they will be able to further deepen their study of the volumes indicated in the 'Course books' section.

Course books

To give non-attending students the opportunity to make up for what is covered during the lessons through independent study, the following materials related to the same content of the program are provided to promote full understanding:

Textbook:

- Pironti, M. (2022). Intelligenze artificiali e aumentate: Elementi di economia e management. EGEA spa.
All chapters (1,2,3,4,5,6,7,8,9) except for chapter 10 (Finance and AI).

Suggested readings:

- Jarrahi, M. H., Askay, D., Eshraghi, A., & Smith, P. (2023). Artificial intelligence and knowledge management: A partnership between human and AI. Business Horizons, 66(1), 87-99.
Available at: https://www.sciencedirect.com/science/article/pii/S0007681322000222

- Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business horizons, 62(1), 15-25.
Available at: https://www.sciencedirect.com/science/article/abs/pii/S0007681318301393
Or: https://www.researchgate.net/publication/328761767_Siri_Siri_in_my_hand_Who's_the_fairest_in_the_land_On_the_interpretations_illustrations_and_implications_of_artificial_intelligence

Assessment

For non-attending students, the same assessment methods as for attending students apply.

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

The slides presented during the lessons, and made available online, will include not only the main content of the textbook but also useful additional information.

Additionally, several articles in English will be uploaded to the Moodle platform for students interested in further exploring certain topics of the course.