Conference paper · 2022
Applications of Artificial Intelligence in Small- and Medium-Sized Enterprises (SMEs)
Cognitive Informatics and Soft Computing: Proceeding of CISC 2021, Lecture Notes in Networks and Systems, vol. 375, pp. 717–726, Springer Nature Singapore · Published
Summary
Borah et al. (2022) reviewed, in a discussion paper without an empirical sample, artificial intelligence (AI) applications in small and medium-sized enterprises (SMEs) and set out the challenges, solutions and advantages of implementing AI in SMEs. They argue that advances in deep learning have made AI important for every enterprise that wants to remain competitive. Some SMEs hesitate to build their own applications because of the cost and duration of AI projects and the resulting high risk of failure, yet SMEs still depend on AI for growth and on cloud-based solutions.
Practical implication. SMEs deterred by the cost, duration and failure risk of building their own AI applications can adopt AI through cloud-based solutions rather than building everything in-house.
- The Problem
- Small and medium-sized enterprises need artificial intelligence to stay competitive, but the cost, duration and failure risk of AI projects make many hesitate.
- The Methodology
- Discussion and review paper on AI applications in SMEs, covering implementation challenges, solutions and advantages; no empirical study is reported in the abstract.
- The Core Finding
- The paper sets out the AI applications relevant to SMEs together with the challenges, solutions and advantages of implementation, concluding that SMEs depend on AI and cloud-based solutions for growth despite the risks.
- The Citation
- Borah, S., Kama, C., Rakshit, S., & Vajjhala, N. R. (2022). Applications of Artificial Intelligence in Small- and Medium-Sized Enterprises (SMEs). In P. K. Mallick, A. K. Bhoi, P. Barsocchi, & V. H. C. de Albuquerque (Eds.), Cognitive Informatics and Soft Computing: Proceeding of CISC 2021 (pp. 717–726). Springer Nature Singapore. https://doi.org/10.1007/978-981-16-8763-1_59
The summary, key findings, methods, implications and relevance notes on this page are this website’s own description of the paper, written from the published abstract and text. The official abstract and citation details are given further down.
Key findings
- Finding 1. Advancements in deep learning have produced new AI applications that make AI important for any enterprise aiming to be competitive, so SMEs — not only technology companies — require AI.
- Finding 2. The paper discusses SME AI applications and identifies the challenges, solutions and advantages of implementing AI in SMEs.
- Finding 3. Some SMEs are concerned about building their own applications because of the cost and length of AI implementation, which brings a high risk of failure.
- Finding 4. Despite these concerns, SMEs still depend on artificial intelligence for growth and on cloud-based solutions.
Source: Borah et al. (2022), Cognitive Informatics and Soft Computing: Proceeding of CISC 2021, Lecture Notes in Networks and Systems, vol. 375, pp. 717–726, Springer Nature Singapore. DOI: 10.1007/978-981-16-8763-1_59
The study in detail
What question does this paper answer?
What artificial intelligence applications are relevant to small and medium-sized enterprises, and what challenges, solutions and advantages accompany AI implementation in SMEs?
What did the study find, in detail?
The paper argues that advances in deep learning have made AI important for every enterprise that wants to remain competitive — not only technology companies but SMEs as well. It discusses SME AI applications and sets out the challenges, solutions and advantages of implementing AI. Some SMEs hesitate to build their own applications because of the cost and duration of AI projects and the resulting high risk of failure, yet SMEs still depend on AI for growth and on cloud-based solutions.
Why does it matter?
Most AI adoption literature focuses on large firms. This paper addresses the resource-constrained SME context, where cost, implementation time and failure risk shape whether and how AI — often through cloud services — is adopted.
Methods and data
| Question | What are the applications, challenges, solutions and advantages of AI in SMEs? |
|---|---|
| Design | Discussion / review paper |
| Context | Small and medium-sized enterprises, in contrast with large technology companies |
| Main points | AI is now important for competitiveness in every enterprise; cost, duration and failure risk deter some SMEs from building their own applications; SMEs rely on AI for growth and on cloud-based solutions |
| Implication | SMEs can adopt AI through cloud-based solutions rather than building everything in-house |
| Citation | Borah et al. (2022) · DOI 10.1007/978-981-16-8763-1_59 |
Abstract
The advancements in deep learning methods have brought several new artificial intelligence (AI) applications making AI important for every enterprise that aims to be competitive. Therefore, not only Tech companies but also small- and medium-sized enterprises (SMEs) require AI. This paper discusses SME AI applications and reveals the challenges, solutions, and advantages of implementing AI in SMEs. Although some SMEs are concerned with building their applications because of the cost and length of implementing AI, resulting in a high risk of failure, nevertheless, SMEs still depend on artificial intelligence for growth and cloud-based solutions.
Abstract as published in Cognitive Informatics and Soft Computing: Proceeding of CISC 2021.
Keywords: Artificial intelligence; Deep learning; Machine learning; SMEs; Efficiency; Development; Applications
Limitations
- A discussion paper (10 pages) without an empirical sample; the abstract reports no data or case evidence.
Practical implications
- Small and medium-sized enterprises (SMEs) can turn to cloud-based solutions to adopt AI instead of building everything in-house.
- SMEs considering building their own AI applications face a cost and length of implementation that, according to the paper, brings a high risk of failure.
- The paper argues that SMEs, and not only technology companies, require AI because advancements in deep learning have made AI important for every enterprise that aims to be competitive.
Drawn from Borah et al. (2022), Cognitive Informatics and Soft Computing: Proceeding of CISC 2021, Lecture Notes in Networks and Systems, vol. 375, pp. 717–726, Springer Nature Singapore.
When this research may be relevant
This paper may be relevant to literature on AI adoption in small and medium-sized enterprises, barriers and enablers of digital transformation in SMEs, cloud-based AI services for smaller firms, and overviews of AI applications in business.
Research topics addressed: artificial intelligence; small and medium enterprises; SMEs; AI adoption; deep learning; machine learning; cloud-based AI; digital transformation; implementation challenges; business competitiveness
How to cite
- APA 7
- Borah, S., Kama, C., Rakshit, S., & Vajjhala, N. R. (2022). Applications of Artificial Intelligence in Small- and Medium-Sized Enterprises (SMEs). In P. K. Mallick, A. K. Bhoi, P. Barsocchi, & V. H. C. de Albuquerque (Eds.), Cognitive Informatics and Soft Computing: Proceeding of CISC 2021 (pp. 717–726). Springer Nature Singapore. https://doi.org/10.1007/978-981-16-8763-1_59
- MLA 9
- Borah, Samarjeet, et al. “Applications of Artificial Intelligence in Small- and Medium-Sized Enterprises (SMEs).” Cognitive Informatics and Soft Computing: Proceeding of CISC 2021, edited by Pradeep Kumar Mallick et al., Springer Nature Singapore, 2022, pp. 717–26. https://doi.org/10.1007/978-981-16-8763-1_59.
- IEEE
- S. Borah, C. Kama, S. Rakshit, and N. R. Vajjhala, “Applications of Artificial Intelligence in Small- and Medium-Sized Enterprises (SMEs),” in Cognitive Informatics and Soft Computing: Proceeding of CISC 2021, P. K. Mallick, A. K. Bhoi, P. Barsocchi, and V. H. C. de Albuquerque, Eds. Springer Nature Singapore, 2022, pp. 717–726, doi: 10.1007/978-981-16-8763-1_59.
BibTeX
@inproceedings{borah2022artificial,
title = {Applications of Artificial Intelligence in Small- and Medium-Sized Enterprises (SMEs)},
author = {Borah, Samarjeet and Kama, Chukwuma and Rakshit, Sandip and Vajjhala, Narasimha Rao},
booktitle = {Cognitive Informatics and Soft Computing: Proceeding of CISC 2021},
series = {Lecture Notes in Networks and Systems},
editor = {Mallick, Pradeep Kumar and Bhoi, Akash Kumar and Barsocchi, Paolo and de Albuquerque, Victor Hugo C.},
pages = {717--726},
year = {2022},
publisher = {Springer Nature Singapore},
doi = {10.1007/978-981-16-8763-1_59},
url = {https://doi.org/10.1007/978-981-16-8763-1_59}
}RIS
TY - CPAPER TI - Applications of Artificial Intelligence in Small- and Medium-Sized Enterprises (SMEs) AU - Borah, Samarjeet AU - Kama, Chukwuma AU - Rakshit, Sandip AU - Vajjhala, Narasimha Rao ED - Mallick, Pradeep Kumar ED - Bhoi, Akash Kumar ED - Barsocchi, Paolo ED - de Albuquerque, Victor Hugo C. T2 - Cognitive Informatics and Soft Computing: Proceeding of CISC 2021 T3 - Lecture Notes in Networks and Systems PY - 2022 DA - 2022/05/31 VL - 375 SP - 717 EP - 726 PB - Springer Nature Singapore SN - 2367-3370 DO - 10.1007/978-981-16-8763-1_59 UR - https://www.narasimharao.net/research/artificial-intelligence-applications-smes/ LA - en ER -
Links and files
- DOI: https://doi.org/10.1007/978-981-16-8763-1_59
- Publisher’s page: https://link.springer.com/chapter/10.1007/978-981-16-8763-1_59
- This page as text: https://www.narasimharao.net/research/artificial-intelligence-applications-smes/paper.md
- Permanent address of this page: https://www.narasimharao.net/research/artificial-intelligence-applications-smes/
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