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Research Paper Volume 8 Issue 3 3513 - 3533 June 21, 2025

Artificial Intelligence in Terms of Business Operations: A Comparative Study of the United States of America, India, and China

Lead author · Corresponding
Anjali Nair
LL.M. student at Symbiosis Law School, Nagpur, India
View PDF Full text DOIhttps://doij.org/10.10000/IJLMH.1110238
Abstract

Artificial intelligence significantly transforms businesses globally, enabling companies to improve their efficiency, enhance customer experience, and focus more on innovation. The data collected for various business operations needs to be protected as enshrined under Article 21 Which was reiterated in a landmark judgment Which expresses information about information security. Artificial Intelligence refers to the use of computers & computer systems that can perform tasks that require human intelligence as learning, problem-solving solving and in terms of decision-making. It’s better used in improving performance with the varied use of applications in different fields as healthcare, finance, transportation, etc. The countries as to India and China has made a significant development in terms of adoption of Artificial Intelligence in the business market wherein, China is regarded as the most advanced country in terms of use of artificial intelligence supported by government initiatives & Indian companies face a lot of challenges as to data protection, regulatory uncertainties etc. When looking at to US, it’s the global leader in adopting AI, as many companies invest heavily in terms of research and development. This paper provides an insight into navigating the complexities faced in the adoption of artificial intelligence in India, China, and the US by highlighting the need for strategies, investments in AI talent, infrastructure, and in bringing up efforts to drive towards AI adoption and innovation.

Type
Research Paper
Information
International Journal of Law Management and Humanities, Volume 8, Issue 3, Page 3513 - 3533
DOI: https://doij.org/10.10000/IJLMH.1110238
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CC BY-NC 4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.
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Copyright © IJLMH 2026
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The views and opinions expressed in this manuscript are those of the author(s) alone and do not reflect the views, policies, or position of the Journal.

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