The evolution of organisational AI readiness toward an orchestration capability

Abstract As Artificial Intelligence (AI) transitions from experimental pilots to enterprise-wide deployment, the central managerial challenge has shifted from simple adoption to the complexities of effective scaling and integration. While existing AI readiness models provide a foundational understanding, they often treat readiness dimensions as static and were created during earlier waves of AI development. This study examines how contemporary deployment conditions, characterised by generative AI, AI-as-a-service and rapidly commoditised infrastructure, reshape what organisational readiness for AI actually entails. Drawing on socio-technical systems theory and dynamic capabilities theory, the study employs an abductive, template-analytic qualitative design combining a literature-derived initial template with fifteen semi-structured interviews with senior practitioners across corporate and Small and Medium companies (SMB) contexts. The analysis indicates that IT infrastructure and data maturity are perceived to have shifted from being differentiators of readiness to being baseline prerequisites, while governance and accountability, process discipline and behavioural alignment have emerged as the primary determinants of effective AI deployment. On this basis the study introduces the construct of Organisational AI Orchestration Capability, defined as the dynamic capacity to integrate, govern and operationalise heterogeneous AI resources, behaviours and processes into reliable enterprise outcomes. The study contributes to information systems research by reframing AI readiness from a static resource inventory to an evolving organisational capability and offers managers a diagnostic logic for sequencing AI investments and avoiding premature scaling.