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

  • Anjali Nair
  • Show Author Details
  • Anjali Nair

    LL.M. student at Symbiosis Law School, Nagpur, India

  • img Download Full Paper

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.

Keywords

  • Artificial Intelligence
  • India
  • China
  • US
  • innovation
  • business operations

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

Creative Commons

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.

Copyright

Copyright © IJLMH 2021