Comparative Analysis of Artificial Intelligence Adoption in Small and Large Companies in Slovenia

Maja Rožman – University of Maribor, Faculty of Economics and Business, Maribor, Slovenia

Polona Tominc – University of Maribor, Faculty of Economics and Business, Maribor, Slovenia

Katja Crnogaj – University of Maribor, Faculty of Economics and Business, Maribor, Slovenia

Abstract: The paper presents a comparative analysis of adopting artificial in­telligence (AI) in small and large companies in Slovenia. The study examines the current landscape of AI usage, including its application in various operational areas such as AI-supported acquiring and retaining talented employees, AI-sup­ported appropriate training and development of employees, and implementa­tion of AI technology in a work environment. A survey was conducted among a sample of small and large companies across different industries in Slovenia. The results provide valuable insights for policymakers, managers, and researchers interested in understanding the dynamics of AI adoption in the Slovenian busi­ness context. Ultimately, this research contributes to the growing body of liter­ature on AI adoption by shedding light on the unique challenges and opportu­nities faced by small and large companies in Slovenia, facilitating informed de­cision-making and strategic planning for future AI implementation initiatives.

7th International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2023 – Selected Papers, Hybrid (Faculty of Organization and Informatics Varaždin, University of Zagreb, Croatia), October 26, 2023

ITEMA Selected Papers published by: Association of Economists and Managers of the Balkans – Belgrade, Serbia

ITEMA conference partners: Faculty of Economics and Business, University of Maribor, Slovenia; Faculty of Organization and Informatics, University of Zagreb, Varaždin; Faculty of Geography, University of Belgrade, Serbia; Institute of Marketing, Poznan University of Economics and Business, Poland; Faculty of Agriculture, Banat’s University of Agricultural Sciences and Veterinary Medicine ”King Michael I of Romania”, Romania

ITEMA Conference 2023 Selected Papers: ISBN 978-86-80194-76-9, ISSN 2683-5991, DOI: https://doi.org/10.31410/ITEMA.S.P.2023

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission.

References

Abrokwah-Larbi, K., & Awuku-Larbi, Y. (2023). The impact of artificial intelligence in mar­keting on the performance of business organizations: evidence from SMEs in an emerging economy. Journal of Entrepreneurship in Emerging Economies, Vol. ahead-of-print No. ahead-of-print. https://doi-org.ezproxy.lib.ukm.si/10.1108/JEEE-07-2022-0207 

Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustain­able manufacturing practices and circular economy capabilities. Technological Forecast­ing and Social Change, 163, 1–16. https://doi.org/10.1016/j.techfore.2020.120420 

Basri, W. (2020). Examining the Impact of Artificial Intelligence (AI)-Assisted Social Media Marketing on the Performance of Small and Medium Enterprises: Toward Effective Busi­ness Management in the Saudi Arabian Context. International Journal of Computational Intelligence Systems, 13(1), 142. https://doi.org/10.2991/ijcis.d.200127.002 

Benjamins, R. (2019). Artificial Intelligence in small and medium-sized enter­prises. Retrieved June 25, 2023, from https://business.blogthinkbig.com/artificial-intelligence-in-small-and-medium-sized-enterprises/  

Cao, L. (2022). A New Age of AI: Features and Futures. IEEE Intelligent Systems, 37(1), 25–37. doi: 10.1109/MIS.2022.3150944.

Dhamija, P., & Bag, S. (2020). Role of artificial intelligence in operations environment: a re­view and bibliometric analysis. The TQM Journal, 32(4), 869–896. https://doi.org/10.1108/TQM-10-2019-0243 

Drydakis, N. (2022). Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic. Information Systems Frontiers, 24(4), 1223-1247. https://doi.org/10.1007/s10796-022-10249-6 

Hansen, E. B., & Bøgh, S. (2021). Artifcial Intelligence and Internet of Things in Small and Medium-Sized Enterprises: A Survey. Journal of Manufacturing Systems, 58(2), 362–372. https://doi.org/10.1016/j.jmsy.2020.08.009 

Kambur, E., & Akar, C. (2022). Human resource developments with the touch of artificial in­telligence: a scale development study. International Journal of Manpower, 43(1), 168–205. https://doi.org/10.1108/IJM-04-2021-0216 

Kedziora, D. J., Musial, K., & Gabrys, B. (2024). AutonoML: Towards an Integrated Framework for Autonomous Machine Learning. Foundations and Trends in Machine Learning, 17(4), 590–766. http://dx.doi.org/10.1561/2200000093 

Liang, D., Cao, W., Zhang, Y., & Xu, Z. (2024). A two-stage classification approach for AI tech­nical service supplier selection based on multi-stakeholder concern. Information Sciences, 652, 119762. https://doi.org/10.1016/j.ins.2023.119762 

OECD. (2020). COVID-19 and Responsible Business Conduct. OECD.

Papadopoulos, T., Baltas, K. N., & Baltac, M. E. (2020). The Use of Digital Technologies by Small and Medium Enterprises During COVID-19: Implications for Theory and Practice. International Journal of Information Management, 55, 102192. https://doi.org/10.1016/j.ijinfomgt.2020.102192 

Peretz-Andersson, E., Tabares, S., Mikalef, P., & Parida, V. (2024). Artificial intelligence imple­mentation in manufacturing SMEs: A resource orchestration approach. International Jour­nal of Information Management, 77, 102781. https://doi.org/10.1016/j.ijinfomgt.2024.102781 

Pillai, R., & Sivathanu, B. (2020). Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations. Benchmarking: An International Journal, 27(9), 2599–2629. https://doi.org/10.1108/BIJ-04-2020-0186 

Szedlak, C., Leyendecker, B., Reinemann, H., Kschischo, M., & Pötters, P. (2021). Risks and Benefits of Artificial Intelligence in Small-and-Medium Sized Enterprises. Proceedings of the International Conference on Industrial Engineering and Operations Management Rome, Italy, August 2-5, 2021. Retrieved June 21, 2023, from http://ieomsociety.org/pro­ceedings/2021rome/175.pdf 

Upadhyay, N., Upadhyay, S., & Dwivedi, Y. K. (2021). Theorizing artificial intelligence ac­ceptance and digital entrepreneurship model. International Journal of Entrepreneuri­al Behavior & Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJEBR-01-2021-0052  

Wang, J., Lu, Y., Fan, S., Hu, P., & Wang, B. (2022). How to survive in the age of artificial intelligence? Exploring the intelligent transformations of SMEs in central China. In­ternational Journal of Emerging Markets, 17(4), 1143–1162. https://doi.org/10.1108/IJOEM-06-2021-0985  

Xu, P., Zhu, X., & Clifton, D. A. (2023). Multimodal Learning With Transformers: A Sur­vey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-20. https://doi.org/10.1109/tpami.2023.3275156  

Zhong, W., Gao, Y., Ding, N., Liu, Z., Zhou, M., Wang, J., Yin, J., & Duan, N. (2023). Im­proving task generalization via unified schema prompt. AI Open, 4, 120–129. https://doi.org/10.1016/j.aiopen.2023.08.011