Artificial Intelligence in SMEs: Enhancing Business Functions Through Technologies and Applications
Artificial intelligence (AI) has significant potential to transform small- and medium-sized enterprises (SMEs), yet its adoption is often hindered by challenges such as limited financial and human resources. This study addresses this issue by investigating the core AI technologies adopted by SMEs, t...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/16/5/415 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850257209462620160 |
|---|---|
| author | Thang Le Dinh Manh-Chiên Vu Giang T.C. Tran |
| author_facet | Thang Le Dinh Manh-Chiên Vu Giang T.C. Tran |
| author_sort | Thang Le Dinh |
| collection | DOAJ |
| description | Artificial intelligence (AI) has significant potential to transform small- and medium-sized enterprises (SMEs), yet its adoption is often hindered by challenges such as limited financial and human resources. This study addresses this issue by investigating the core AI technologies adopted by SMEs, their broad range of applications across business functions, and the strategies required for successful implementation. Through a systematic literature review of 50 studies published between 2016 and 2025, we identify prominent AI technologies, including machine learning, natural language processing, and generative AI, and their applications in enhancing efficiency, decision-making, and innovation across sales and marketing, operations and logistics, finance and other business functions. The findings emphasize the importance of workforce training, robust technological infrastructure, data-driven cultures, and strategic partnerships for SMEs. Furthermore, the review highlights methods for measuring and optimizing AI’s value, such as tracking key performance indicators and improving customer satisfaction. While acknowledging challenges like financial constraints and ethical considerations, this research provides practical guidance for SMEs to effectively leverage AI for sustainable growth and provides a foundation for future studies to explore customized AI strategies for diverse SME contexts. |
| format | Article |
| id | doaj-art-e7ad1f4330be4aa08b2e3177db5b5643 |
| institution | OA Journals |
| issn | 2078-2489 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj-art-e7ad1f4330be4aa08b2e3177db5b56432025-08-20T01:56:28ZengMDPI AGInformation2078-24892025-05-0116541510.3390/info16050415Artificial Intelligence in SMEs: Enhancing Business Functions Through Technologies and ApplicationsThang Le Dinh0Manh-Chiên Vu1Giang T.C. Tran2Research Institute on SMEs, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, CanadaAccounting Sciences Department, Université du Québec en Outaouais, Gatineau, QC J8X 3X7, CanadaResearch Institute on SMEs, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, CanadaArtificial intelligence (AI) has significant potential to transform small- and medium-sized enterprises (SMEs), yet its adoption is often hindered by challenges such as limited financial and human resources. This study addresses this issue by investigating the core AI technologies adopted by SMEs, their broad range of applications across business functions, and the strategies required for successful implementation. Through a systematic literature review of 50 studies published between 2016 and 2025, we identify prominent AI technologies, including machine learning, natural language processing, and generative AI, and their applications in enhancing efficiency, decision-making, and innovation across sales and marketing, operations and logistics, finance and other business functions. The findings emphasize the importance of workforce training, robust technological infrastructure, data-driven cultures, and strategic partnerships for SMEs. Furthermore, the review highlights methods for measuring and optimizing AI’s value, such as tracking key performance indicators and improving customer satisfaction. While acknowledging challenges like financial constraints and ethical considerations, this research provides practical guidance for SMEs to effectively leverage AI for sustainable growth and provides a foundation for future studies to explore customized AI strategies for diverse SME contexts.https://www.mdpi.com/2078-2489/16/5/415artificial intelligenceSMEAI-powered technologies |
| spellingShingle | Thang Le Dinh Manh-Chiên Vu Giang T.C. Tran Artificial Intelligence in SMEs: Enhancing Business Functions Through Technologies and Applications Information artificial intelligence SME AI-powered technologies |
| title | Artificial Intelligence in SMEs: Enhancing Business Functions Through Technologies and Applications |
| title_full | Artificial Intelligence in SMEs: Enhancing Business Functions Through Technologies and Applications |
| title_fullStr | Artificial Intelligence in SMEs: Enhancing Business Functions Through Technologies and Applications |
| title_full_unstemmed | Artificial Intelligence in SMEs: Enhancing Business Functions Through Technologies and Applications |
| title_short | Artificial Intelligence in SMEs: Enhancing Business Functions Through Technologies and Applications |
| title_sort | artificial intelligence in smes enhancing business functions through technologies and applications |
| topic | artificial intelligence SME AI-powered technologies |
| url | https://www.mdpi.com/2078-2489/16/5/415 |
| work_keys_str_mv | AT thangledinh artificialintelligenceinsmesenhancingbusinessfunctionsthroughtechnologiesandapplications AT manhchienvu artificialintelligenceinsmesenhancingbusinessfunctionsthroughtechnologiesandapplications AT giangtctran artificialintelligenceinsmesenhancingbusinessfunctionsthroughtechnologiesandapplications |