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Initiating transformation towards AI in SMEs
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
2020 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Purpose – The purpose is to explore how SMEs can initiate transformation towards AI. The purpose will be fulfilled through identifying which opportunities that exist for SMEs and which challenges they are facing. Additionally, we will identify which requirements are necessary to face these challenges.

Method – A qualitative approach was most suitable for this study since the purpose is to explore how SMEs can initiate transformation towards AI. It was also suitable since we have collected data through interviews. We have done a single case study where we have studied one supply chain. Finally, we have had an inductive research approach which means that we have gathered a theoretical background which has founded the base and the background for our study, but our interviews have founded the result of the study and created a conclusion based on that.

Findings –The result of the study provides identified opportunities with AI for SMEs, what challenges can occur, and which requirements that are needed to face the challenges. The opportunities are identified as forecasting, maintenance and repair, self-optimization, and tracing and tracking. The identified challenges when initiating transformation towards AI are cultural difficulties, lack of external communication, lack of internal communication, limited internal processes, and lack of resources. The requirements are identified as automation, data, strategy, and capabilities. The opportunities, challenges and requirements are summarized in a framework.

Theoretical and Managerial Implications – We have contributed to literature by exploring how an SME, as a mass production company, can benefit from AI by identifying opportunities, challenges, and requirements. Additionally, the framework guides SMEs to prepare for opportunities with AI and ensure that they have all of the requirements. Further, by understanding which requirements that are necessary for a transformation and which challenges that can occur, managers can reduce risk of failing projects.

Limitations and Future Research –The number of studied companies together with that the study is a single case study limits the generalizability. It creates a suggestion for future research where a wider set of data can be collected. Additionally, we have identified challenges that can occur, however how companies should face these challenges in the best way is a suggestion for future research.

Place, publisher, year, edition, pages
2020. , p. 51
Keywords [en]
Manufacturing Processes, Artificial Intelligence, SME, Mass production, Digital Transformation, Smart Manufacturing, Industry 4.0.
National Category
Business Administration
Identifiers
URN: urn:nbn:se:ltu:diva-79343OAI: oai:DiVA.org:ltu-79343DiVA, id: diva2:1438217
Educational program
Industrial and Management Engineering, master's level
Supervisors
Examiners
Available from: 2020-06-12 Created: 2020-06-10 Last updated: 2025-10-22Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • Other style
More styles
Language
  • de-DE
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  • nn-NB
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  • Other locale
More languages
Output format
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  • asciidoc
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