1
An Analytical review on the Impact of Artificial Intelligence on
the Business Industry: Applications, Trends, and Challenges
Kuldeep Gurjar
1
Department of Computer Science, Kangwon National University, Chuncheon, Republic of Korea
2
The University of Suwon, Hwaseong, Republic of Korea
Email: dkekuldeep@gmail.com
Anshika Jangra
Department of Research and Clinical Coordination,
CureTherapeutics Inc., Suwon, Republic of Korea
Email: anshika.jangra@curetherapeutics.com
Hasnan Baber*
School of Business Administration,
American University of Sharjah, Sharjah, United Arab Emirates
Email: hbaber@aus.edu
https://orcid.org/0000-0002-8951-3501
*Corresponding Author
Maidul Islam
Department of International Business, Keimyung Adams College (KAC),
Keimyung University, Daegu, Republic of Korea
Email: maidul@kmu.ac.kr
Shabnam Abdulkasem Sheikh
International College, The University of Suwon,
Gyeonggi-do, Hwaseong-Si, Republic of Korea
Email: shabnam@suwon.ac.kr
Abstract
The integration of artificial intelligence (AI) in business processes has revolutionized many
industries by automating tasks, improving decision-making processes, and enhancing customer
experiences. This review paper examines the impact of AI in business areas, including its
applications, challenges, limitations, current trends, and future work. The paper begins with
defining the importance of AI in business, followed by an overview of its applications in various
sectors such as customer service, marketing, finance, healthcare, manufacturing, logistics, and
human resources. The advantages and benefits of AI implementation are explored, along with
examples of successful AI implementation and changes in business processes. The challenges and
limitations of AI technology, such as ethical concerns, data privacy and security issues, technical
expertise and knowledge, and high implementation costs, are explained. Current trends in AI
integration, such as the integration of AI with other technologies, the growing demand for AI
skills, and the development of more advanced and sophisticated AI algorithms, are presented.
This article has been accepted for publication in IEEE Engineering Management Review. This is the author's version which has not been fully edited and
content may change prior to final publication. Citation information: DOI 10.1109/EMR.2024.3355973
© 2024 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.
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