Artificial intelligence – AI – allows continual and, to some extent, autonomously driven change in organizations, with a constant inflow of data, updated and self-learning algorithms, and hence use processes that change on a recurring basis. The project examines this dynamic from a broader perspective that also encompasses how AI use processes are influenced by, and in turn influence, governance, resource allocation and strategies for AI.

The premise is that AI technologies differ in multiple ways from conventional resources, given the broad application space, potentially major impacts, and partially autonomous actions. Therefore, it cannot be assumed that AI can be governed by traditional means; but rather that it gives rise to a distinctive dynamic in which AI use and AI governance impact each another. This may promote organizational learning and increase the scope for utilizing the opportunities AI offers, but can also lead to rigidity, stagnation and fragmentation.

By examining these processes, the project aims to contribute knowledge on how the desired AI applications can be furthered while avoiding destructive unintentional consequences. The project is thus expected to contribute to a more nuanced and realistic discussion on the role that AI can and should play in organizations of the future, and how this can be influenced.

The overall topics addressed by the project are:

• How does the direct use and governance of AI evolve over time, and why?
• How does the dynamic between AI use and governance impact organizational development and renewal?

To answer these questions, the researchers intend to apply perspectives from multiple disciplines, including information systems, innovation, organization theory, and sociology. Given that AI differs considerably from traditional IT by virtue of its self-learning nature, these processes will be monitored empirically using a number of methods. These include in-depth field studies, surveys, comparative case studies, and experiments.

The researchers also plan knowledge exchange beyond the academic community: At the end of the project, its findings will be integrated into tailored leadership programs and MOOCs, in the form of case studies, short explainer videos and case insights. This will enable empirically grounded, actionable knowledge to become readily available to organizations in the private and public sectors.

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Affiliated with WASP-HS

This project is affiliated with WASP-HS and generously funded by the Marianne and Marcus Wallenberg Foundation.

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Principal Investigator(s)

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Project Member(s)