SUCCESS CONDITIONS FOR ORGANIZATIONAL AI IMPLEMENTATIONS

This article examines why many AI implementations, despite substantial investments and increasing technological maturity, have so far generated only limited sustainable organizational value. Drawing on current empirical studies, relevant literature, and the author's prior work, it argues that the so-called AI value gap cannot be understood solely as a technological problem. Rather, the findings suggest that organizational readiness, workflow integration, data quality, governance, change management, and digital as well as AI-related competencies are central prerequisites for successful AI transformation. The article positions competency models as instruments for systematically integrating AI-related requirements into role profiles, human resource development, leadership development, and organizational development. Technical, strategic, communicative, and ethical competency dimensions are discussed as key elements of an expanded competency concept. The article is designed as a conceptual literature and discussion paper linking implementation research with competency-based management approaches.