Institute
Institute for Artificial Intelligence in Business and Management
The institute examines how companies integrate artificial intelligence into their strategic and operational development. It asks where AI can make a demonstrable contribution to customer value, value creation and competitiveness, and what conditions are needed. Drawing on the St. Gallen Integrated Management Concept, it considers strategy, organisation, processes, people and technology together. It researches how companies select suitable applications, develop existing business models and design new products and services. Economic benefits are considered alongside the effects on collaboration, decision quality and responsibility. This connects technology choices with concrete questions of business leadership and management.
A further focus is implementation: how do tasks, roles and workflows change when people work with AI systems? The institute examines how to assess productivity and quality, which capabilities employees and leaders need, and how organisations learn from individual applications. It also studies how AI use is governed, including clear responsibilities, appropriate human oversight and the handling of data, risks and system limitations. The aim is to understand the conditions under which AI can be used reliably in everyday work and its impact can be evaluated.
Current research priorities
AI strategy and business models
Examining how companies assess potential AI applications by their strategic contribution, customer value and economic viability, and use this assessment to set priorities for existing and new business models.
Process transformation and productivity
Analysing how AI changes tasks and workflows, and under what conditions it can improve time efficiency, quality and resource use across the entire process.
Human-AI collaboration
Researching how tasks, roles and decision rights are designed for collaboration between people and AI systems, and which capabilities are needed.
AI-supported decisions
Examining how leaders assess AI-generated analyses and proposed courses of action, combine them with experience and specialist knowledge, and explain decisions while remaining accountable for them.
AI governance and responsibility
Examining how clear responsibilities, human oversight and transparent rules for data, quality and risks support the responsible use of AI.
Organisation and implementation
Researching how companies build capabilities, support change and use lessons from AI applications to develop their organisation and management practices.