Assessment of role of the Artificial Intelligence and Machine Learning in Business Enterprises

Authors

  • Naveen Kumar  Wipro Limited, East Brunswick, New Jersey, USA

DOI:

https://doi.org/10.32628/CSEIT2174139

Keywords:

Artificial intelligence (AI), Business, Machine Learning (ML), Enterprise.

Abstract

AI and ML in practice are discussed in this paper to analyse how these technologies affect business operations in various industries. Artificial Intelligence and Machine Learning, concepts which for a long time were a part of theory only, are now essential to develop organizational performance and minimize the burden of various tasks as well as optimize decision making. In the present paper, reviewing a vast amount of the relevant literature, the author explains the advantages of AI and ML, including higher productivity, lower costs, and higher customer satisfaction; at the same time, the listed disadvantages, including poor data quality, adaptation of employees, and ethical issues, are also mentioned. It covers industries such as finance, healthcare, retail, manufacturing, and many others to demonstrate how AI & ML disrupt conventional approaches and unveil innovative sources of competitiveness. The paper also covers the future of AI and focuses on existing hurdles that inhibit the utilization of these technologies in businesses.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2021-08-30

Issue

Volume 7, Issue 4, July-August-2021

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Naveen Kumar, " Assessment of role of the Artificial Intelligence and Machine Learning in Business Enterprises " International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 4, pp.655-665, July-August-2021. Available at doi : https://doi.org/10.32628/CSEIT2174139