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




TekijätJafarzadeh, Pouya; Vähämäki, Tanja; Nevalainen, Paavo; Tuomisto, Antti; Heikkonen, Jukka

KustantajaSpringer Nature

Julkaisuvuosi2024

JournalJournal of Technology Transfer

ISSN0892-9912

eISSN1573-7047

DOIhttps://doi.org/10.1007/s10961-024-10122-5

Verkko-osoitehttps://link.springer.com/article/10.1007/s10961-024-10122-5

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/457336151


Tiivistelmä

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.


Ladattava julkaisu

This is an electronic reprint of the original article.
This reprint may differ from the original in pagination and typographic detail. Please cite the original version.




Julkaisussa olevat rahoitustiedot
Open Access funding provided by University of Turku (including Turku University Central Hospital).


Last updated on 2025-27-01 at 19:27