Artificial Intelligence and Knowledge Integration in Firms : A Comparative Qualitative Study of AI Adoption in Sweden and Ghana

Sammanfattning

Artificial Intelligence (AI) is revolutionizing the business world’s decision making, knowledge creation, and innovation at an increasing pace. Although contemporary literature focus on technical advantages and obstacles as well as innovation improvements, limited research exists on how firms experience the influence AI has on knowledge related work. Specifically, how AI influences knowledge creation and integration in organizations, and whether the experience and context based knowledge held by employees is threatened by this development. Thus, this research focuses on how firms view AI’s influence on knowledge creation and its integration in the context of multinational firms. The research utilizes a multi-case qualitative methodology through semi-structured interviews with Swedish and Ghanaian professionals connected to AI implementation strategy, knowledge management, and human resources. Thereby giving an overview of AI’s effect on employee development from their perspective. Drawing upon the knowledge-based view of the firm and human-AI co-evolution model, the research examines six mechanisms in which AI influences knowledge creation and integration processes: Replacing Codification Paradox with Co-Evolution, Domain Knowledge Integration as Prerequisite for Knowledge Creation, Organizational Learning and Accumulation of Knowledge, The Integration Challenge: Striking a Balance between Standardization and Context Preservation, Knowledge Integration and Workforce Capability Development, and Leadership, Trust and Knowledge Preservation. The findings suggest that firms view AI as a complementary tool rather than replacement for human employees. Successfully utilizing AI seems to rely heavily on trust, human judgment and experience, contextual knowledge, national culture, and organizational culture. The study suggests a broader difference between Swedish and Ghanaian firms in their AI implementation, workforce development strategy, and trust in AI output. Although AI streamlines simpler tasks improving efficiency as well as knowledge storage, innovation, and organizational learning, there are still concerns about data integrity, future displacement risks, accountability ambiguity, and contextual knowledge and experience preservation. This research contributes empirically to limited qualitative research on AI’s effect on knowledge creation and integration within multinational firms. It explores the perspectives of firm professionals with overview of knowledge transfer and evolution within companies in Sweden and Ghana. It first presents a framework based on contemporary literature to explain the current understanding of AI adoption and its effect on knowledge creation and integration, before reconceptualizing the framework after analyzing the empirical data. Instead of a mere technological implementation process, the reconceptualized framework presents AI adoption as a socio-technical process influenced by national culture, company culture, trust, leadership, and human-AI co-evolution. The findings contribute to contemporary literature, policy-makers, and decision-makers with perspectives on AI knowledge integration from knowledge-related work professionals. Thus, suggesting a human-in-the-loop approach to AI implementation in line with socio-technical and co-evolution theories rather than substitution.