Organizational Culture & Algorithmization: How can we explain their fit?

Organizational culture shapes various organizational characteristics, i.e. processes, and advantages of different organizational cultures depend on the context and goals of the organization. In this theoretical work, we propose that this principle also holds true concerning algorithmization, i.e., the process of AI selection, introduction and implementation in organizations. Yet, prevailing notions in AI implementation often assume that only organizations with innovative cultures are suited to successfully adopt AI, while others are presumed less capable of introducing AI. In this theoretical contribution, we challenge this assumption. We synthesize existing theoretical models of organizational culture and organization-technology fit - focusing on the Competing Values Framework, and synthesize it with the human-organization-technology-fit model - to develop the CHAiO (Culture-Human-AI-Organization) framework. This framework offers a conceptual and practical approach for how different organizational cultures can achieve a “fit” with algorithmization. We review current research on organizational culture in the context of AI adoption, and formulate testable hypotheses that clarify how organizational culture influences AI implementation. Based on the theoretical synthesis, no culture is inherently better suited for AI adoption; rather, each culture type requires tailored algorithmization strategies. This conceptual paper (1) challenges the assumption that innovation alone determines AI readiness, (2) advances a nuanced perspective on culture-AI fit and (3) provides practical insights for organizations aiming to navigate AI implementation. The importance of understanding organizational culture as a critical factor for algorithmization is highlighted, offering a foundation for future research on organizational factors influencing successful AI implementation.