Joint Programme in Digital Transformation

During the spring semester 2027, various courses concerning digital transformation will be offered by the ten partner universities. See the course catalogue here.

• Teaching institution: University of St.Gallen
• Lecturer: Prof. Dr. Jan Marco Leimeister and Dr. Andreas Janson
• Date: 28 – 29 May 2027 & 4 – 5 June 2027
• Course number: tbc
• Course title: Cloud and Enterprise AI Transformation
• ECTS: 6 ECTS
• Accreditation: The HSG Course "Cloud and Entreprise AI Transformation" course is automatically accredited (for HSG students) to your "electives" (Wahlbereich) for all HSG Master Students exept MBI Students - in the MBI the course will be automatically credited to the "core electives" (Pflichtwahlbereich). The remaining 14 ECTS won't be credited to your HSG Curriculum. 
• Certificate: You will be receiving a seperate Certificate in Digital Transformation after you have passed and completed three virtual courses as well as the summer seminar. The certificate will be awarded by a seniour representative of ENGAGE.EU at the end of the summer seminar.

HSG Course Abstract

This course examines the cloud and compute infrastructure underlying enterprise artificial intelligence, and the managerial decisions that this infrastructure imposes on the firm during digital transformation processes.

Organizations deploying AI at scale confront a recurring set of decisions: the allocation of workloads across providers and deployment models; the choice between internal development, procurement, and partnership; the selection of use cases suitable for automation; the justification of multi-year commitments under uncertainty regarding future compute and inference costs; the transition from pilot implementations to production systems; and the degree of dependence on a limited number of providers and jurisdictions that the firm is prepared to accept. Such decisions are costly to reverse and constrain the organization over extended periods.

The course proceeds in four sessions:

• Session 1 addresses the architecture of the cloud and AI stack, including emerging interoperability mechanisms such as MCP, and the economic mechanisms operating in infrastructure markets: economies of scale, learning effects, network effects, switching costs, data gravity, and commoditization.
• Session 2 addresses the business case, covering sourcing arrangements, AI unit economics (including token economics and FinOps), and the assessment of automation candidates.
• Session 3 addresses organizational implementation, including adaptation beyond adoption, MLOps and value streams, cloud/AI operating models, production scaling, and agentic AI.
• Session 4 addresses digital sovereignty as a design dimension, covering concentration risk, exit costs, control points, and relevant architectural, contractual, compliance, risk, security, and operational-resilience considerations (including DORA).