A study of AI as a new strategic imperative; challenging existing strategies, business models and organizational processes
The national focus on artificial intelligence (Ministry of Trade and Industry, N2018.14) emphasizes that AI has the potential to contribute significant value in a number of areas through increased economic growth, as well as solutions to environmental and social challenges.
There are a number of challenges associated with AI in both private and public operations. This project aims to create a platform for developing knowledge about key challenges in the implementation of new AI solutions. Challenges that are in focus in the implementation of AI solutions are of three different types: 1) challenges in business development processes when translating AI-generated big data analyzes into value-creating services, 2) the need for new organizational and business models when AI is implemented and 3) strategic and structural issues, including distribution of responsibilities and control of AI-related activities.
The strategic challenges also include issues related to the general market development connected to AI and the implementation of new business models (“AI-as-a-Service”). Based on the creation of a new multi-industrial platform and “think tank”, the project will develop new knowledge across industry boundaries focusing on these AI challenges, both practically and theoretically.
The project consists of three parts: an AI Business Lab, an empirical, basic research part and a knowledge integration part, each consisting of work packages. Up to four companies in different industries are initially connected to the knowledge platform and its business development and implementation focus. One part consists of a knowledge integration package where knowledge from the research part and the business development part is integrated. The basic research part of the project aims to develop new, deep knowledge of the connection between strategy, business model development and organization when new AI-based solutions are developed and implemented, something that has been defined as an important knowledge gap in existing AI research.
Principal investigator: Per Andersson, Professor, SSE Institute for Research
Co-project leader: Christopher Rosenqvist, Associate Professor, SSE Institute for Research