Integrating Artificial Intelligence Governance into Business Excellence: A Design-Oriented Capability Framework for Small and Medium-Sized Enterprises in Emerging Europe

Organizations that pursue business excellence increasingly rely on data-intensive and automated decision support. At the same time, managers face widening expectations regarding accountability, transparency, and societal impact when deploying artificial intelligence (AI). This paper develops a compact, design-oriented capability framework that helps small and medium-sized enterprises (SMEs) integrate AI governance into the continuous improvement routines of established excellence models. Building on an integrative synthesis of business excellence, Quality 4.0, and AI governance standards and policy guidance, the study translates high-level principles into auditable management practices that are feasible under resource constraints and high vendor dependence. The framework specifies six governance capabilities: (1) leadership accountability, (2) risk and impact assessment, (3) lifecycle controls for data and models, (4) transparent documentation, (5) human oversight and skills, and (6) ecosystem and supplier management. These capabilities are mapped to excellence dimensions and operationalized through a maturity rubric and decision templates that support readiness assessment and investment prioritization. The contribution is the integration logic: rather than proposing new AI governance principles, the paper shows how SMEs can embed existing governance requirements into excellence-based planning, audit, and corrective-action cycles while making trade-offs explicit for emerging European ecosystem contexts.