Paradigm of Artificial Intelligence in Business Management

Year : 2024 | Volume :14 | Issue : 01 | Page : 26-30

Shikha Deshmukh Gavhade

  1. Assistant Professor Department of Electronics and Communication, Corporate Institute of Management, Bhopal Madhya Pradesh India


Artificial intelligence stands out as a prominent trend in today’s technological landscape, enabling machines to engage in human-like thinking, learning from experiences, adapting to new inputs, and making decisions. This capability facilitates rapid and error-free results, akin to human rational decision-making. In the contemporary business landscape, which is often regarded as a cornerstone for national development, artificial intelligence plays a pivotal role. Businesses, ranging from small-scale enterprises to medium-sized ones (SMBs), are reaping the benefits of AI by reducing costs, enhancing performance, bolstering security, and efficiently monitoring various business functions. These aspects are crucial for the establishment and sustenance of businesses within the economy. To deal with such issues, artificial intelligence can work as a catalyst. The main objective of this work is to attain competitive advantage and analyze the profit of adopting AI in business firms for their intensification and development. The rapid advancement of artificial intelligence is compelling strategists to reconfigure business models, leading to the widespread incorporation of AI into various business processes. This trend provides valuable insights into the deployment and consequences of AI for business leaders, managers, technology developers, and implementers. The exploration encompasses considerations of cultural heritage values and risk assessments for conservation and mitigation. Additionally, it delves into the evaluation of onshore and offshore technological capabilities, incorporating spatial equipment to address marketing and retail strategies, as well as applications in insurance and healthcare systems.

Keywords: Artificial intelligence, machines, business strategies, innovation, business

[This article belongs to Current Trends in Information Technology(ctit)]

How to cite this article: Shikha Deshmukh Gavhade. Paradigm of Artificial Intelligence in Business Management. Current Trends in Information Technology. 2024; 14(01):26-30.
How to cite this URL: Shikha Deshmukh Gavhade. Paradigm of Artificial Intelligence in Business Management. Current Trends in Information Technology. 2024; 14(01):26-30. Available from:


  1. Kshetri N. Opportunities and challenges of artificial intelligence in business. Int J Entrep Behav Res. 2018; 24(2): 292–307.
  2. Tucci L. (2024). A guide to artificial intelligence in the enterprise. Enterprise AI. [Online]. TechTarget. Available from: ‌
  3. Singh N. (2023). Role of Artificial intelligence in Business Management. [Online]. Aeologic Blog. Available from: ‌
  4. Caflou. (2024). The Use of AI in Business Management. [Online]. Caflou. Available from: ‌
  5. McCarthy John, Minsky ML, Rochester N, Shannon CE. A proposal for the Dartmouth summer research project on artificial intelligence, August 31, 1955. AI Mag. 2006; 27(4): 12.
  6. Caflou. Firschein O, Fischler MA, Coles LS, Tenenbaum JM. Forecasting and assessing the impact of artificial intelligence on society. In IJCAI’73: Proceedings of the 3rd international joint conference on Artificial intelligence. 1973 Feb; 5(1): 105–120.
  7. Cockburn Iain M, Rebecca Henderson, Scott Stern. The Impact of Artificial Intelligence on Innovation. The Economics of Artificial Intelligence: An Agenda. NBER Working Paper No. 24449. 2019; 115–152.
  8. Soni Neha, Sharma EK, Singh Narotam, Kapoor Amita. Impact of Artificial Intelligence on Business. Digital Innovations, Transformation, and Society Conference 2018 (Digits 2018). 2018; 10p.
  9. Park Sang-Chul. The Fourth Industrial Revolution and implications for innovative cluster policies. AI Soc. 2018; 33(4): 433–445.
  10. Mazali Tatiana. From industry 4.0 to society 4.0, there and back. AI Soc. 2018; 33(3): 405–411.
  11. Gulli Antonio, Amita Kapoor. TensorFlow 1. x Deep Learning Cookbook: Over 90 unique recipes to solve artificial intelligence driven problems with Python. Birmingham, United Kingdom; 2017.
  12. Elo S, Kyngäs H. The qualitative content analysis process. J Adv Nurs. 2008 Apr; 62(1): 107–15.

Regular Issue Subscription Review Article
Volume 14
Issue 01
Received January 25, 2024
Accepted March 15, 2024
Published April 3, 2024