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Digital Transformation: the world beyond AI

General data

Course ID:	4003-DTAI-ERASMUS
Erasmus code / ISCED:	14.6 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0312) Political sciences and civics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Digital Transformation: the world beyond AI
Name in Polish:	Digital Transformation: the world beyond AI
Organizational unit:	Centre for Europe
Course groups:	Courses in foreign languages Courses in foreign languages for Erasmus students Courses only for Erasmus students General university courses
ECTS credit allocation (and other scores):	6.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.
Language:	(unknown)
Type of course:	general courses
Mode:	Blended learning
Short description:	The aim of this course is to show the changes brought by the digitalisation of business activities. The massive arrival of AI will have a disruptive and multiplier effect. The class will analyse these two phenomena using examples.
Full description:	We are going to analyse the different types of digital transformation and see how they impact the different business sectors. We're going to integrate the paradigm shift brought about by the arrival of generative AI to try and imagine the future of the different businesses. To understand digital transformation, we will use a framework built around the following variables: Customer, Data, Innovation Platforms, Follow up. Structure of the course : What is digital transformation ? A brief history of the Internet AI : what it is and how to take profit of it – How to use ChatGPT efficiently (a method will be given) Transformation Coverage Examples Beginning to define the value proposition dStrategies for adaptation How to identify needs and prepare a transformation plan A framework for transformation : a. Customer b. Data c. Innovation d. Platforms e. Strategic models and. KPIS How to organise and follow up a transformation project What you need to know about technology how to organise change management
Bibliography:	D.L. Rogers, The Digital Transformation Playbook, Columbia Business School, 2016 D.L. Rogers, The Digital Transformation Roadmap, Columbia Business School, 2023 J. Knapp, Sprint : how to solve big problems and test new ideas in just five days, Simon&Schuster, 2016 T. Saldanha, Why Digital Transformations Fail: The Surprising Disciplines of How to Take Off and Stay Ahead, Berrett-Koehler Publishers, 2019 The impact ou AI on jobs : https://cepr.org/voxeu/columns/impact-artificial-intelligence-growth-and-employment International Labour Organization report : Generative AI and Jobs: A global analysis of potential effects on job quantity and quality : https://www.ilo.org/wcmsp5/groups/public/---dgreports/---inst/documents/publication/wcms_890761.pdf
Learning outcomes:	At the end of the course, students should be able to understand all the dimensions of digital transformation, and identify the needs and gaps in current transformations. They will be able to identify the different types of transformation and have a global view of the technologies used today. They should be able to understand the impact of AI on their own future.
Assessment methods and assessment criteria:	Students will work in small groups (3 people, 4 maximum) on a topic proposed in the first session. During the course, they will have moments dedicated to this work through questions that they will have to answer. These questions will be presented during the course and will be closely linked to the subjects covered during the course. The last session will be dedicated to the presentation of the results by the different groups. (power point support + oral presentation, 15 to 20 min). Classe attendance, presentation of the chosen use case and in-class activity and involvement in the use case.

Classes in period "Summer semester 2023/24" (in progress)

Time span:	2024-02-19 - 2024-06-16	Selected timetable range: weekly course term Navigate to timetable MO TU WYK W TH FR
Type of class:	Lecture, 15 hours, 25 places more information
Coordinators:	Dorota Jurkiewicz-Eckert, Joanna Pomian
Group instructors:	Joanna Pomian
Students list:	(inaccessible to you)
Examination:	Course - Grading Lecture - Grading

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