AI deployment challenges often arise from misalignments between technological design and the social systems into which it is introduced. Drawing on Bostrom and Heinen’s (1977a) Socio-Technical Systems framework, this study analyses contemporary AI literature to identify the root causes of recurring failures. The work adapts the framework into a diagnostic tool that links socio-technical conditions to common AI challenges, offering both a conceptual lens for research and practical guidance for governance and design. While literature-based, the framework provides a foundation for empirical testing to improve proactive, context-sensitive AI integration.