Acquiring Competitive Advantages Through AI Capabilities

Abstract

This thesis aims to explore how knowledge-intensive firms in Denmark can leverage AI capabilities to gain competitive advantages, refining existing theory. Existing literature suggests that engaging in situating activities, including grounding, bounding, and recasting, leads to gaining competitive advantages with AI capabilities. These activities enable AI capabilities to be tailored to specific firms, reducing development costs, and ensuring environmental fit, fulfilling criteria that are necessary for competitive advantage, including value, rarity, inimitability, and the inability to be substitutable. However, the key drivers and implications of these activities remain unclear, encouraging this thesis to analyze insights from interviews with AI professionals. A qualitative approach is thus applied in this thesis, followed by a thematic analysis of the data retrieved. The findings emphasize the importance for firms to understand the drivers behind competitive advantages stemming from situating activities, particularly focusing on data quality and quantity. In addition, one of the implications identified in engaging in the situating activities, is the affection of stakeholder relationships. It can thus be concluded that companies can acquire competitive advantages with AI capabilities by engaging in situating activities, however, it is crucial to recognize that data quality and quantity significantly influence the level of competitive advantage achieved, while the implications may affect the sustainability of such advantages, requiring firms to remain aware.