Title: StrateGAIze: A Study on How Generative AI Can Support Board Decision-Making in Strategic Matters

Authors: Filip Andersson & Elton Carlsson Published:

2024-05-21

Supervisor: Jonas Gabrielsson

Background: Boards are responsible for the organization and its strategic direction. This involves adapting and reevaluating strategies to maintain and enhance the organization’s competitive advantages. Thus, the board's effectiveness is a crucial aspect of the company's success. Today’s business world is characterized by vast amounts of data and rapid changes, making it challenging for boards to make well-informed strategic decisions. Large volumes of data and a lack of time have been shown to lead to cognitive limitations, preventing fully rational decisions. Generative AI has emerged as a powerful new technology capable of addressing these challenges. By processing and analyzing extensive datasets and providing additional insights, generative AI can facilitate board decision-making.

Purpose: The purpose of this study is to explain and understand the potential of generative AI as an aid to enhance board members' decision-making in strategic matters.

Research question: What function can generative AI serve in supporting board members' decision-making processes in strategic matters?

Method: A qualitative research method was used in this study, where ten board members from start-up-sized to publicly traded companies were interviewed, all of whom use generative AI. The data was analyzed using an abductive approach, combining both deductive and inductive research methods to create a deeper understanding of the phenomenon.

Conclusion: The study's conclusions show that generative AI can offer efficiency benefits in board members' decision-making processes in strategic matters. The conclusion outlines the specific functions that generative AI can have to support board members. However, the conclusion also indicates that it is currently challenging for board members to stay updated on new technology, such as generative AI. The study results in a model illustrating an effective task distribution between board members and generative AI, contributing theoretical and practical knowledge about the function generative AI can serve in optimizing board work.