Conceptual model enhances ai readiness in smes, addressing key barriers and suggesting practical solutions.
(SMEs) must embrace artificial intelligence (AI) to remain competitive in an AI-driven business landscape. However, challenges such as limited resources, insufficient AI expertise, and inadequate data infrastructures often impede successful AI adoption. This paper proposes that AI organisational readiness is a critical determinant of effective AI implementation in SMEs. Through a comprehensive literature review and analysis of existing frameworks, this study develops a novel conceptual model integrating five interconnected dimensions: Strategic Readiness, Organisational Readiness, Technological Readiness, Capability Readiness, and Ecosystem Readiness. Each dimension is tailored to address SMEs’ specific needs and constraints, emphasising foundational digital capabilities as a prerequisite for AI readiness. The model includes a flexible assessment methodology and implementation framework adaptable to diverse SME contexts based on size, AI maturity, and industry. A comparative analysis highlights SMEs’ agility in AI adoption compared to larger organisations’ scale-driven approaches, tempered by unique challenges like ethical governance and data quality. By offering a holistic approach to assessing and enhancing AI readiness, this paper contributes to both theory and practice in AI adoption for SMEs. The proposed model provides researchers with a robust framework for studying AI readiness in SMEs and equips practitioners with practical guidance to maximise AI-driven outcomes. This paper presents a conceptual framework, acknowledging that empirical validation is beyond its scope but critical for future research to ensure practical applicability.
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Kalleparambil et al. (2025) studied this question.
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