Understanding Drivers and Outcomes of AI Adoption: A Theory-Elaboration Approach
通过访谈AI专家和分析现场报告，识别了影响企业采纳AI的内外部因素，并扩展了TOE框架，揭示了AI对组织敏捷性和可持续绩效的影响。
Nowadays, companies face different challenges due to marketization, the global health crisis, and political instability. The environment is thus changing continually. Firms should be able to adapt to change and leverage it as a means of progress. Moreover, Artificial Intelligence (AI) is transforming current jobs significantly and creating new ones. To survive in the long run, companies must be able to adopt and utilize AI effectively. In this paper, we explore the antecedents and outcomes of AI adoption at the firm level through a qualitative study based on semi-structured interviews with AI experts and field reports analysis. These experts' interviews and triangulated field evidence have allowed a high level of research rigor. Findings reveal that AI adoption is influenced by internal factors related to leadership and governance, innovation, data management, algorithmic depth, performance, and external ones, socially, ethically, and ecologically. Indeed, we've extended the TOE Framework as part of a theory elaboration approach by adding new antecedents of AI adoption and shedding light on its impact on organizational agility and sustainable performance. The paper provides engineering managers with best practices that can help when performing AI projects, and researchers with a theoretical Framework that can be studied in different contexts.