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Article . 2025
License: CC BY
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Article . 2025 . Peer-reviewed
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Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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AI in SMEs - A holistic approach for successful implementations

Authors: Didunoluwa Olukoya; Paschal Alumona; Stanley Chinedu Okoro; Abdulaziz O Ibiyeye; Saadat O Ibiyeye; Mark Onons Ikhifa;

AI in SMEs - A holistic approach for successful implementations

Abstract

Small and medium-sized enterprises (SMEs) are the backbone of global economic growth, and they still to a great extent does not comprehend the advantages brought about by the artificial intelligence (AI) technology as compared to large companies. Studies that have been previously conducted in this area recognize quite a number of hurdles such as the lack of finance, poor data quality, unavailability of skilled personnel, and unwillingness to change the way of doing things but still very little research has been done in this area and no comprehensive models have been proposed that integrate these factors. This article creates a comprehensive framework of seven pillars indicating that the SMEs would be ready for the implementation of the AI technology, synthesizing insights from empirical research, conceptual models, and high-impact industry reports. The study utilized a structured literature review whereby the researcher's pinpointed gaps, inconsistencies, and unresolved debates in the past works, and ultimately camouflaged all these manifestations into seven different readiness dimensions namely; strategic, organizational, data, technical, human, financial, and ethical readiness. The refined pillars do not overlap but clearly indicate what their role is in SME AI adoption thus ensuring good demarcation of the strategic areas that are suitable for supporting AI adoption in SMEs. This paper also provides visual illustrations to explain the interplay of the pillars as a unified system. The study later reveals new avenues for research and among them is the need for operational, sector-specific implementation guides for SMEs which are not found in the current literature thus urging the researchers to conduct further studies on this topic.

Keywords

Structured Literature Review, Technology Adoption Barriers, SME Readiness, AI Readiness Framework, Digital Transformation, Artificial Intelligence Adoption

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green