Potential Applications of AI in Manufacturing SMEs: A Literature Review and Case Studies

Sergio Salimbeni (), Rudolf Grünbichler, Sarah Wagner, Matías Bonacina, Julieta Gutnisky and Sofía Maid
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Sergio Salimbeni: USAL, Universidad del Salvador, Research & Development Department, Institute of Art, Design, Architecture and Technology
Rudolf Grünbichler: TUG, University of Technology, Faculty of Mechanical Engineering and Economic Sciences, Institute of Business Economics and Industrial Sociology
Sarah Wagner: TUM, Technical University of Munich, Institute for Machine Tools and Industrial Management. Bavaria
Matías Bonacina: USAL, Universidad del Salvador, Research & Development Department, Institute of Art, Design, Architecture and Technology
Julieta Gutnisky: USAL, Universidad del Salvador, Research & Development Department, Institute of Art, Design, Architecture and Technology
Sofía Maid: USAL, Universidad del Salvador, Research & Development Department, Institute of Art, Design, Architecture and Technology

Chapter 4 in Industry 5.0 for SMEs, 2026, pp 99-145 from Springer

Abstract: Abstract Small and medium-sized enterprises are under constant competitive pressure, forcing them to adopt a more proactive attitude towards efficiency and innovation. Emerging technologies are not only changing the manufacturing sector, but are also having a profound impact on society. One of the most notable technologies is artificial intelligence (AI). While the integration of AI in SMEs is complex and holds significant potential to improve decision-making processes along the value chain and across all operational functions, there are other exponential technologies such as the Internet of Things (IoT). Other exponential technologies such as the Internet of Everything and digital twins amplify these benefits when used in conjunction with AI. The aim of this study is to identify the application potential of AI in manufacturing SMEs. To achieve this, a literature review was conducted. Application potentials as well as application examples from manufacturing SMEs were identified and evaluated. Through analysing 69 relevant papers, it highlighted 10 potential application areas and 13 feasible applications fields, including forecasting, process optimization, and customer service automation. The findings suggest that AI can enhance productivity, cost reduction, flexibility, and decision making across various SME departments. In addition, the potential of AI is demonstrated using three illustrative application examples.

Keywords: Artificial intelligence; SMEs; Industry 5.0; AIoE; Application (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-26279-0_4

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