Abstract
Artificial intelligence (AI) technologies have gained in significance for all types of firms, including family-influenced firms. However, despite their idiosyncratic motives, little is known about the issues family-influenced firms face in adopting complex and knowledge intensive technologies, such as AI. Peculiar characteristics of AI technologies—specifically, autonomy, learning, and inscrutability— present both opportunities and challenges to family-influenced firms. To explore how family-influenced firms approach AI technologies, we adopt a social capital perspective and combine inductive qualitative and deductive quantitative research into a mixed methods design. In the first step, we conducted a multiple case study of eight case firms consisting of rich data from 112 interviews and additional archival documents. Building on within-case and cross-case pattern analysis, we reveal opposing implications of external social capital and (internal) family social capital on the adoption of AI. While external network ties with suppliers, customers, and competitors help overcome the challenges due to the unique aspects of AI technologies, family influence exacerbate those challenges. In the second step, we sought to test the conceptual framework that we developed with our multiple case study. Based on large-scale data from 1,444 firms, we find empirical support that increasing levels of external social capital with regard to suppliers, customers, and competitors drive AI adoption. Moreover, we find that family influence has a negative moderating effect on the relationships between supplier, customer, and competitor ties on the one hand and AI adoption on the other hand. Our study contributes toward a nuanced understanding of the idiosyncratic challenges of AI adoption faced by family-influenced firms, the role of both external and family social capital in this regard, and how and why AI-related characteristics cause owning families to exacerbate the AI adoption-related challenges.