A Review of AI and ML Adoption in Businesses Worldwide

Authors

  • Nithyananda B Devadiga Assistant Professor, Department of Computer Science, R N Shetty PU College, Kundapura, Karnataka, India Author

DOI:

https://doi.org/10.32628/IJSRST24114136

Keywords:

AI, Business Development, ML, Emerging Technology, Digitalisation, Sustainable Development

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are the two emerging technologies adopted by most of the business companies worldwide. The use of advanced technologies is highly effective on businesses and capable of improving overall performance of companies. Examining the potential effects, opportunities, challenges and scopes of adopting AI and ML in businesses worldwide is the main purpose of this study. In regard to this, secondary qualitative methods have been used for gathering authentic and reliable data from several scholarly articles and peer-reviewed journals. All the findings are discussed briefly and it has been identified that AI and ML have great influence towards workplace efficiency, productivity and profitability of business companies. It also helps to boost customer satisfaction and gain competitiveness in the global market.

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References

Canhoto, A. I., & Clear, F. (2020). Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential. Business Horizons, 63(2), 183-193.https://bura.brunel.ac.uk/bitstream/2438/19258/3/FullText.pdf DOI: https://doi.org/10.1016/j.bushor.2019.11.003

Cioffi, R., Travaglioni, M., Piscitelli, G., Petrillo, A. and De Felice, F., 2020. Artificial intelligence and machine learning applications in smart production: Progress, trends, and directions. Sustainability, 12(2), p.492. Doi:10.3390/su12020492 DOI: https://doi.org/10.3390/su12020492

Colantonio, L., Equeter, L., Dehombreux, P., & Ducobu, F. (2021). A systematic literature review of cutting tool wear monitoring in turning by using artificial intelligence techniques. Machines, 9(12), 351.https://doi.org/10.3390/machines9120351 DOI: https://doi.org/10.3390/machines9120351

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. DOI: 10.1016/j.ijinfomgt.2019.08.002 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.08.002

Helo, P., & Hao, Y. (2022). Artificial intelligence in operations management and supply chain management: An exploratory case study. Production Planning & Control, 33(16), 1573-1590. DOI: 10.1080/09537287.2021.1882690 DOI: https://doi.org/10.1080/09537287.2021.1882690

Kelly, S., Kaye, S. A., & Oviedo-Trespalacios, O. (2022). What factors contribute to acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 101925.https://doi.org/10.1016/j.tele.2022.101925 DOI: https://doi.org/10.1016/j.tele.2022.101925

Kitsios, F., & Kamariotou, M. (2021). Artificial intelligence and business strategy towards digital transformation: A research agenda. Sustainability, 13(4), 2025.. https://doi.org/10.3390/su13042025 DOI: https://doi.org/10.3390/su13042025

Lee, J., Suh, T., Roy, D., & Baucus, M. (2019). Emerging technology and business model innovation: the case of artificial intelligence. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 44. Doi:10.3390/joitmc5030044 DOI: https://doi.org/10.3390/joitmc5030044

Uren, V., & Edwards, J. S. (2023). Technology readiness and the organizational journey towards AI adoption: An empirical study. International Journal of Information Management, 68, 102588. https://doi.org/10.1016/j.ijinfomgt.2022.102588 DOI: https://doi.org/10.1016/j.ijinfomgt.2022.102588

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Published

25-08-2024

Issue

Section

Research Articles

How to Cite

A Review of AI and ML Adoption in Businesses Worldwide. (2024). International Journal of Scientific Research in Science and Technology, 11(4), 393-399. https://doi.org/10.32628/IJSRST24114136

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