“Learning by changing”: A dual-case study on the knowledge orchestration in developing enterprise situated-AI capabilities
通过对两家中国中小企业的双案例研究，发现企业通过“边变边学”机制，经历感知认知、获取技术、创造知识、重构经验四个阶段，将通用AI技术转化为情境化AI能力，为管理者规划数字化转型提供参考。
While more firms realize that only applying standardized and general AI technology cannot bring AI capability, the capability building in organizational dimension remain unexplored. This study aims to answer the question “How do enterprises build situated-AI capabilities?” With a dual-case study of two Chinese SMEs, this paper found a knowledge orchestration which transforming AI resources into organizational capabilities. The mechanism of absorbing AI technology and turning it into organizational capabilities is like “learning by changing”, with undergoing organizational change, through four stages: sensing their own managerial cognition, seizing situation-specific AI technology, creating situated-AI knowledge and technology, and re-configuring management experiential cognition. These conclusions contributes in developing theories related to situated AI, and in enriching the theoretical content of knowledge orchestration. In practical, this findings brings insights on planing and managing enterprise digital and intelligent transformation in perspective of AI capability building and organizational learning.