The Crossroads of AI & Innovation Management

Important results from the project

The aim of the project has been to contribute to an increased understanding of the connection between AI and innovation management from a practitioner and academic perspective. An exploratory study based on in-depth interviews with 23 people from 18 AI-related innovation projects was performed. The contribution lies primarily in the discussion about how AI-related innovation projects build on established innovation management practices and about where there seems to be particular innovation management needs linked to AI-related innovation projects.

Expected long term effects

Eleven categories of impact factors were identified, primarily representing factors known from the traditional innovation context and that are normally associated with more radical innovation. Preliminary results indicate that complexity and infrastructure are two factors that have considerable impact when conducting AI-related innovation. The results also highlight the importance of established innovation management practice in AI-related innovation as well as provide the basis for future research at the crossroads of AI and Innovation Management.

Approach and implementation

To enable unexpected discoveries, an exploratory approach was chosen where in-depth interviews and group discussions of preliminary results formed the core of the project. The selection of AI projects for study was made after the project’s start in consultation with Vinnova, which resulted in a broad representation of various AI-related innovation projects, actors and application areas. An exploratory approach and late project selection led to some required redefinitions, and delayed the analysis work but also allowed for the most interesting results.