Artificial Intelligence: From Data to Insights : Artificial Intelligence in Digital Transformation Strategies in the Semiconductor Industry

Abstract: Emerging technologies are reshaping the digital landscape and competitive environment of highly technological companies with the introduction of artificial intelligence (AI). Firms are reacting by implementing digital transformation (DT) strategies aligning the organizational and technological factors towards leveraging AI-generated information. This thesis sheds new light on the topics of knowledge management (KM), DT, and AI in organizational practices with an emphasis on AI-enhanced software-as-a-service (SaaS). The research results in a conceptual framework, designed from the literature on AI, DT, KM, and dynamic capability view (DCV) uncovering three overarching concepts (internal capabilities, absorptive capacity, and technological competitiveness). This conceptual framework was then complemented by empirical data featuring primary data gathered from a single case study and secondary data from an internet-mediated data collection. The interviews in the case study were focused on managers with extensive experience in the semiconductor industry and operators working with the AI-enhanced SaaS tool. The analysis concludes in an updated conceptual framework, highlighting the interplay of a firm’s internal capabilities and an AI-enhanced absorptive capacity indicating three pathways toward achieving technological competitiveness in a highly technological environment. Additionally, a proposed solution is presented featuring an AI-enhanced tool operator as a new role, responsible for supporting organization-wide activities with AI-generated information.