Supporting SME companies in mapping out AI potential: a Finnish AI development case

Pouya Jafarzadeh (), Tanja Vähämäki (), Paavo Nevalainen (), Antti Tuomisto () and Jukka Heikkonen ()
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Pouya Jafarzadeh: University of Turku
Tanja Vähämäki: University of Turku
Paavo Nevalainen: University of Turku
Antti Tuomisto: University of Turku
Jukka Heikkonen: University of Turku

The Journal of Technology Transfer, 2025, vol. 50, issue 3, No 9, 1016-1035

Abstract: Abstract Products and services relying upon Artificial Intelligence (AI) have moved from mere concepts to reality. However, challenges still exist in applying AI technologies to traditional industrial and service enterprises. Two central problems are a proper understanding of the opportunities AI could bring to the business processes and making the business logic and data sources transparent to AI experts. As small and medium-sized enterprises (SMEs) are considered the economic backbone of many countries, this paper studies how to support SMEs in understanding the potential of AI in their business and how to prepare their data and requirements for a possible AI project. For this purpose, we first proposed the Cross-Industry Standard Process for Data Mining (CRISP-DM) an industry-proven way to apply AI solutions. The weight was in early business and data understanding. Then, we performed data visualization and developed some machine learning methods for 11 SMEs in South-western Finland as case studies to get more ideas for improving their business using AI. Two surveys probed the possible changes in AI practises of companies.

Keywords: Artificial intelligence; Business; Development; collaboration; Small and medium sized enterprises (search for similar items in EconPapers)
JEL-codes: O33 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10961-024-10122-5

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