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Investigating the Potential of AutoML as an Instrument for Fostering AI Adoption in SMEs

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Knowledge Management in Organisations (KMO 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1593))

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Abstract

Artificial Intelligence (AI) has emerged as a mature and value-adding technology in business. Yet, its adoption is often challenging, due to both a lack of financial resources as well as staff. Particularly small and mid-sized enterprises (SME) risk to be left behind. AutoML, an instrument that helps automate certain AI tasks and thus reduces the need for dedicated staff, promises to overcome some of these AI adoption challenges. Investigating this problem space, the given paper reports on the results of a study exploring AI strategies, initiatives and obstacles SMEs in Germany, Austria and Switzerland face, and how AutoML may help with them. Results from an interview study with representatives from 12 different manufacturing companies suggest that AutoML can facilitate AI adoption, especially to overcome limited data science expertise and to enable prototyping. In this, it may further support strategic decision-making and create awareness for AI-driven innovation. Yet, a basic level of AI majority is required for AutoML to tap its full potential.

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Notes

  1. 1.

    Online: https://www.gartner.com/smarterwithgartner/2-megatrends-dominate-the-gartner-hype-cycle-for-artificial-intelligence-2020/ [accessed: January 14th 2022].

  2. 2.

    Online: https://jupyter.org/ [accessed: January 14th 2022].

  3. 3.

    Online: https://colab.research.google.com/ [accessed: January 14th 2022].

  4. 4.

    Note: Hyperparameters define the working of the ML algorithm and through this significantly influence the performance of the algorithm for a given ML problem.

  5. 5.

    Online: https://ec.europa.eu/growth/smes/sme-definition_en [accessed: January 14th 2022].

  6. 6.

    Online: https://www.maxqda.com/ [accessed: January 14th 2022].

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Authors and Affiliations

  1. Department of Management, Communication and IT, MCI – The Entrepreneurial School, Universitätsstraße 15, 6020, Innsbruck, Austria

    Stephan Olsowski, Stephan Schlögl, Ellen Richter & Reinhard Bernsteiner

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  1. Stephan Olsowski
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  2. Stephan Schlögl
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  3. Ellen Richter
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  4. Reinhard Bernsteiner
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Correspondence to Stephan Schlögl .

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  1. Staffordshire University, Stoke-on-Trent, UK

    Lorna Uden

  2. University of Kaohsiung, Kaohsiung, Taiwan

    I-Hsien Ting

  3. FernUniversität in Hagen, Hagen, Germany

    Birgit Feldmann

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Olsowski, S., Schlögl, S., Richter, E., Bernsteiner, R. (2022). Investigating the Potential of AutoML as an Instrument for Fostering AI Adoption in SMEs. In: Uden, L., Ting, IH., Feldmann, B. (eds) Knowledge Management in Organisations. KMO 2022. Communications in Computer and Information Science, vol 1593. Springer, Cham. https://doi.org/10.1007/978-3-031-07920-7_28

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