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Artificial Intelligence and industrial transformations

Funded by: Marianne and Marcus Wallenberg Foundation, within the WASP-HS initiative
Time period: 2021-2026
Project members: KTH/ Industrial Economics and Management
Project contact persons:

Background:

This project aims to explore how the technology shift to artificial intelligence (AI) and autono­mous systems might transform the technology-based industry in Sweden. Through history, breakthroughs of general-purpose technologies, such as AI, have shown to be significantly dif­ficult to handle for established corporations. Thus, how will a breakthrough of AI affect the Swedish incumbent corporations?

Depending on how AI is applied, it could symbiotically strengthen existing businesses, or disrupt established companies, creating new industry logics and opportunities for new compe­titors to emerge. Drawing on theories from socio-technical transition and innovation manage­ment, the project brings a social science perspective on the phenomenon of AI and autonomous systems.

The following research questions are addressed:

  1. How will AI, as a general-purpose technology, change the Swedish industry?
  2. How will incumbent firms manage the AI-based technological shift?
  3. What roles will intermediaries and new entrants have in AI-driven industrial transfor­mations?
  4. How and under which conditions will established industry survive AI-driven transfor­ma­tions in Sweden?

The project deploys a qualitative research approach, aiming to create a repertoire of real-world examples representing different logics and different consequences of AI-implementation. The idea is to map the phenomenon and conduct multiple case studies of three types of actors; in­cum­bent firms; “intermediaries” (e.g. consultancy companies), and new entrants.

By addressing AI-implementation in different contexts and under different conditions, the pro­ject brings insights on the dynamics behind AI-based technology shifts, as well as how, and under which conditions, companies might succeed (or fail) when adapting AI-technologies. The aim is to contribute to theory building by developing concepts capturing significant aspects of these dynamics.

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Belongs to: Industrial Economics and Management
Last changed: Jun 03, 2022
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