Artificial Intelligence (AI) Maturity in Small and Medium-Sized Enterprises: A Framework of Internalized and Ecosystem-Embedded Capabilities
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866912957347135488 |
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| author | Sawang, Sukanlaya Sornlertlamvanich, Virach |
| author_facet | Sawang, Sukanlaya Sornlertlamvanich, Virach |
| contents | Artificial intelligence (AI) maturity models have proliferated, yet prevailing frameworks remain largely enterprise-centric, linear, and weakly aligned with the organizational realities of small and medium-sized enterprises (SMEs). This study develops a conceptual AI maturity framework explicitly grounded in SME contexts. Drawing on organizational capability theory, maturity model research, and the SME digital transformation literature, the framework reconceptualizes AI maturity as a multidimensional, non-linear, and ecosystem-embedded capability. It comprises eight interrelated capability dimensions, five maturity levels, and four archetypal development pathways, capturing heterogeneity in SME AI adoption trajectories. By foregrounding resource constraints, informal governance, owner-manager dominance, and external ecosystem dependence, the framework extends existing AI maturity theory and responds to calls for context-sensitive conceptualization of AI capability development. The study provides a foundation for future empirical validation and comparative research on AI maturity in SMEs, to measure their competitiveness, potential in self-development, and driving force in the SME context. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_08728 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Artificial Intelligence (AI) Maturity in Small and Medium-Sized Enterprises: A Framework of Internalized and Ecosystem-Embedded Capabilities Sawang, Sukanlaya Sornlertlamvanich, Virach Computers and Society C.m MISCELLANEOUS Artificial intelligence (AI) maturity models have proliferated, yet prevailing frameworks remain largely enterprise-centric, linear, and weakly aligned with the organizational realities of small and medium-sized enterprises (SMEs). This study develops a conceptual AI maturity framework explicitly grounded in SME contexts. Drawing on organizational capability theory, maturity model research, and the SME digital transformation literature, the framework reconceptualizes AI maturity as a multidimensional, non-linear, and ecosystem-embedded capability. It comprises eight interrelated capability dimensions, five maturity levels, and four archetypal development pathways, capturing heterogeneity in SME AI adoption trajectories. By foregrounding resource constraints, informal governance, owner-manager dominance, and external ecosystem dependence, the framework extends existing AI maturity theory and responds to calls for context-sensitive conceptualization of AI capability development. The study provides a foundation for future empirical validation and comparative research on AI maturity in SMEs, to measure their competitiveness, potential in self-development, and driving force in the SME context. |
| title | Artificial Intelligence (AI) Maturity in Small and Medium-Sized Enterprises: A Framework of Internalized and Ecosystem-Embedded Capabilities |
| topic | Computers and Society C.m MISCELLANEOUS |
| url | https://arxiv.org/abs/2603.08728 |