Diagnosing Human–AI Fit in Mid-Market Operating Systems: A Viable-System Alignment Model

Mid-market firms now share operational judgment with machine-learning systems while remaining too small to staff enterprise-grade governance. Viability theory and recent taxonomies of AI-era organizational pathologies explain why that combination is structurally demanding; they do not yet supply a diagnostic of fit between the human activity system and the model. This article describes the diagnostic. Following a design-science process on the practice-to-theory path, the Viable-System Alignment Model (VSAM) was specified by reanalysis of a theoretically sampled mid-market archive documented between 2003 and 2025. The original archive showed recurring and subsequently stable patterns concerning observation, authority, written judgment, and coordination load, which were reanalyzed as candidate conditions of human–AI fit. The artifact comprises Observability, Decision Rights, Codification, and Metabolic Load, each with a home in the Viable System Model and a socio-technical failure mode. The central proposition is that human–AI fit is a property of the viable system rather than of the software itself. Evaluation at this stage is analytical and descriptive rather than observational; independent field evaluation is reserved for subsequent research.