An analytical framework for business leaders to assess SMEs’ readiness for AI adoption

Purpose This study introduces a practical analytical framework that enables Small and Medium-sized Enterprises (SMEs) leaders to assess their business’s readiness to adopt Artificial Intelligence (AI) technologies across key business dimensions, prioritise resource allocation and manage the adoption process effectively. Design/methodology/approach The authors employed an integrative review of contemporary AI Readiness literature to synthesise existing theoretical perspectives into a six-dimensional AI Readiness Analytical Framework, including: Business Strategy, Resource Orchestration, Skills and Knowledge, Ethical Practice, Culture and Data Management, followed by direct validation and feedback from 17 business leaders, primarily from SMEs. Findings The proposed AI Readiness Analytical Framework is validated as both theoretically robust and practically relevant, with all dimensions rated highly in terms of importance by the SME leaders. Strategy is ranked as the most important dimension, highlighting the need for clear vision, leadership, defined use cases and effective change management. Resource Orchestration is ranked lowest, reflecting SMEs’ preference for accessible, low-cost AI tools; however, resource requirements are expected to increase as AI adoption matures. Originality/value This study introduces a leadership-centred AI Readiness Analytical Framework tailored to SMEs that addresses gaps in large-enterprise models. Its originality lies in both the validation of the framework by SME leaders and the positioning of Ethical Practice as a standalone dimension. The framework functions as both a diagnostic and strategic tool, enabling proactive, capability-aligned AI adoption.