AI Affecting Local Search in Strategic Decision-Making

Abstract

Artificial intelligence technologies could be used to direct executives’ scarce attention to improve the quality of decision making and in particular, improve strategic search. However, use of such technologies could also amplify bias or induce local search. We draw from literature on local search as well as literature on managerial implications of AI technologies to specify how the use of AI technologies could affect search in the context of strategic decision-making. We propose that AI tools can broaden search space, change cognitive-attentional dynamics of the search process, or affect interpretation of cues. We further detail what factors are likely to affect this, including managerial, organizational and industry characteristics. We thus contribute to the literature on local search by detailing how technologies might alleviate or aggravate the situation, and to literature on AI technologies by providing guidance on how these technologies could be used in the strategy process in an optimal way.