AI Adaption within SMEs: Analysis of Impedances and Suggested Approaches

In this paper, we present the main obstacles faced by small and medium-sized enterprises (SMEs) when implementing artificial intelligence (AI), and suggest a novel “plug and play” guided approach for further integration. In order to identify the relevant barriers, we first compile results from recent literature reviews that address challenges specific to SMEs and AI. Then, based on the AI maturity model for SMEs by Schuster et al. [1], we analyze the current status of AI in local German SMEs with which we have worked in the context of the “KI-Labor Südbaden”[2] project. Based on the results of the analysis, we detail a structured approach utilizing pre-identified successful AI implementations as the basis for further technological development. By structuring their AI integration on known successful use cases, SMEs have the chance to leapfrog their AI development and remain competitive in today’s landscape.

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Publication Details

Journal
Opus-HSO (Offenburg University of Applied Sciences)
Published
2024-10-18
DOI
https://doi.org/10.60643/urai.v2024p143
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

AI Adaption within SMEs: Analysis of Impedances and Suggested Approaches

Opus-HSO (Offenburg University of Applied Sciences)
Digital Transformation in Industry
article

AI Adaption within SMEs: Analysis of Impedances and Suggested Approaches

article en

Abstract

In this paper, we present the main obstacles faced by small and medium-sized enterprises (SMEs) when implementing artificial intelligence (AI), and suggest a novel “plug and play” guided approach for further integration. In order to identify the relevant barriers, we first compile results from recent literature reviews that address challenges specific to SMEs and AI. Then, based on the AI maturity model for SMEs by Schuster et al. [1], we analyze the current status of AI in local German SMEs with which we have worked in the context of the “KI-Labor Südbaden”[2] project. Based on the results of the analysis, we detail a structured approach utilizing pre-identified successful AI implementations as the basis for further technological development. By structuring their AI integration on known successful use cases, SMEs have the chance to leapfrog their AI development and remain competitive in today’s landscape.

Opus-HSO (Offenburg University of Applied Sciences)
Offenburg University of Applied Sciences (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 53%
Digital Transformation in Industry
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