Shodh Sari-An International Multidisciplinary Journal
Vol-03, Issue-01 (Jan-Mar 2024)
An International scholarly/ academic journal, peer-reviewed/ refereed journal, ISSN : 2959-1376
Artificial Intelligence and Its Impact on Economic Growth
Choudhary, Sanju
Assistant Professor in Computer Science, F.G.M. Govt. College, Adampur (Hisar), Haryana
DOI: https://doi.org/10.59231/SARI7676
Subject: Economics / Computer Science / Information Technology
Page No.356-368
Received: Dec 06, 2023
Accepted: Dec 26, 2023
Published: Jan 01, 2024
Thematic Classification: Artificial Intelligence (AI), Economic Growth, Digital Economy, Automation and Labor, Productivity Enhancement, Technological Innovation, GDP Drivers, Future of Work, Haryana Economic Perspective.
Abstract
Artificial intelligence (AI) has risen as a paramount force, fundamentally altering the contours of the contemporary economy. Its transformative potential transcends industries, promising to reshape them and serve as a catalytic agent for economic expansion. This research paper embarks on an exploration of the multifaceted dimensions of AI’s influence on economic growth. We delve into its profound contributions, dissecting the impact it has on productivity, innovation, labor markets, and the disruptive waves it sends through industries. With a keen eye on the path ahead, we navigate the challenges and opportunities that AI bestows upon policymakers, businesses, and society at large. A central theme that threads through this examination is the paramount importance of nurturing sustainable and inclusive economic development in the AI era. Through a meticulous analysis of the current landscape of AI adoption and its potential ramifications, our goal is to shed light on the trajectory that AI-driven economic growth is poised to take, offering valuable insights for shaping a future where AI’s transformative power benefits all.
Keywords: AI technology, Economic growth, Innovation, Policymakers, Infrastructure.
Impact Statement
The research on artificial Intelligence and it’s impact on economic growth, dissecting the intricate web of opportunities and obstacles that this transformative technology for presents. AI serve as a well spring of innovation in locking novel possibilities across sectors that were previously unimaginable. Policy makers need to address the digital divide to ensure that business of all size and regions have access to AI resources. AI may automate some roles, it’s also it’s transform others many jobs new require collaboration with AI system, which necessitates new skill sites. For instance, data scientists and AI ethicists are in high demand to develop and oversee AI technology AI applications in a particular life science discipline or interdisciplinary sitting.
About Author
Sanju Chaudhary is working as Assistant Professor of computer science in F.G.M Govt College Adampur Hisar. She has published various research papers in National and International Journals. She has attended several conferences, seminars and workshops.
Cite this Article
APA 7th Style: Choudhary, S. (2024). Artificial intelligence and its impact on economic growth. Shodh Sari-An International Multidisciplinary Journal, 3(01), 356–368. https://doi.org/10.59231/SARI7676
Chicago 17th Style: Choudhary, Sanju. “Artificial Intelligence and Its Impact on Economic Growth.” Shodh Sari-An International Multidisciplinary Journal 3, no. 1 (2024): 356–368. https://doi.org/10.59231/SARI7676.
MLA 9th Style: Choudhary, Sanju. “Artificial Intelligence and Its Impact on Economic Growth.” Shodh Sari-An International Multidisciplinary Journal, vol. 3, no. 1, 2024, pp. 356-368, https://doi.org/10.59231/SARI7676.
Statements & Declarations
Review Method: This article underwent a double-blind peer-review process by independent experts in Computer Science and Economics to evaluate the correlation between AI integration and macroeconomic indicators such as productivity, labor market shifts, and GDP growth.
Competing Interests: The author, Sanju Choudhary, declares that there are no financial, personal, or professional conflicts of interest that could have inappropriately influenced the research findings or the interpretation of the economic data presented.
Funding: This research was conducted through the academic support of the Department of Computer Science, F.G.M. Govt. College, Adampur (Hisar). No specific external grants or commercial funding were received for this study.
Data Availability: The analysis is based on a review of global AI adoption trends, automation statistics, and economic growth models. All secondary data sources and empirical studies referenced are cited within the manuscript.
License: Artificial Intelligence and Its Impact on Economic Growth © 2024 by Sanju Choudhary is licensed under CC BY-NC-ND 4.0. This work is published by the International Council for Education Research and Training (ICERT).
Ethics Approval: As this study is a theoretical and systematic review of technological and economic trends and does not involve direct human or animal experimentation, it was deemed exempt from formal institutional ethical review while maintaining strict adherence to research integrity.
References
Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics. DH. Why are there still so many jobs? The history and future of workplace automation, 11(4), 959–975. Autor. https://doi.org/10.1016/j.joi.2017.08.007
Agarwal, R. (2023). Use of technology by higher education students. Shodh Sari-An International Multidisciplinary Journal, 02(4), 152–161. https://doi.org/10.59231/SARI7631
Bécue, A., Praça, I., & Gama, J. (2021). Artifcial intelligence, cyber-threats and Industry 4.0: Challenges and opportunities. Artificial Intelligence Review, 54(5), 3849–3886. https://doi.org/10.1007/s10462-020-09942-2
Bourne, C. (2019). AI cheerleaders: Public relations, neoliberalism and artifcial intelligence. Public Relations Inquiry, 8(2), 109–125. https://doi.org/10.1177/2046147X19835250
Coglianese, C., & Lehr, D. (2017). Regulating by robot: Administrative decision making in the Machinelearning era. Georgetown Law Journal, 105, 1147–1223.
Lu, H., Li, Y., Chen, M., Kim, H., & Serikawa, S. (2018). Brain intelligence: Go beyond artifcial intelligence. Mobile Networks and Applications, 23(2), 368–375. https://doi.org/10.1007/s11036-017-0932-8
Mhlanga, D. (2020). Industry 4.0 in Finance: The Impact of Artificial Intelligence (AI) on Digital Financial Inclusion. International Journal of Financial Studies, 8(3), 45. https://doi.org/10.3390/ijfs8030045
Mishra, S., & Gupta, S. K. (2023b). Atal tinkering labs and the global notion of STEM education. Shodh Sari-An International Multidisciplinary Journal, 02(4), 131–137. https://doi.org/10.59231/SARI7629
Pintér, J., Fels, M., Lycon, D. S., Meeuwig, J. W., & Meeuwig, D. J. (1995). An intelligent decision support system for assisting industrial wastewater management. Annals of Operations Research, 58(6), 455–477. https://doi.org/10.1007/BF02032381
Ryman-Tubb, N. F., Krause, P., & Garn, W. (2018). How Artificial Intelligence and machine learning research impacts payment card fraud detection: A survey and industry benchmark. Engineering Applications of Artificial Intelligence, 76, 130–157. https://doi.org/10.1016/j.engappai.2018.07.008
Syam, N., & Sharma, A. (2018). Waiting for a sales renaissance in the fourth Industrial Revolution: Machine learning and artificial intelligence in sales research and practice. Industrial Marketing Management, 69, 135–146. https://doi.org/10.1016/j.indmarman.2017.12.019
Tang, X., Li, X., Ding, Y., Song, M., & Bu, Y. (2020). The pace of artificial intelligence innovations: Speed, talent, and trial-and-error. Journal of Informetrics, 14(4), 101094. https://doi.org/10.1016/j.joi.2020.101094
Faithpraise, F. O., Otosi, F. B., Idika, D. O., Efiong, J. E., Udie, C. A., & Orji, E. I. (2023). Advocacy of AI skills acquisition a panacea for youth unemployment in South–South Nigeria. Shodh Sari-An International Multidisciplinary Journal, 02(4), 190–206. https://doi.org/10.59231/SARI7634
Wolff, J. G. (2014). Big data and the SP theory of intelligence. IEEE Access, 2, 301–315. https://doi.org/10.1109/ACCESS.2014.2315297
Xue, L., Zhu, Y. P., & Xue, Y. (2013). RAEDSS: An integrated decision support system for the regional agricultural economy in China. Mathematical and Computer Modelling, 58(3–4), 480–488. https://doi.org/10.1016/j.mcm.2011.11.002
Yamashiro, S. (1986). Online secure-economy preventive control of power systems by pattern recognition. IEEE Transactions on Power Systems, 1(3), 214–219. https://doi.org/10.1109/TPWRS.1986.4334984
Yong, B., Xu, Z. J., Wang, X., Cheng, L. B., Li, X., Wu, X., & Zhou, Q. G. (2018). IoT-based intelligent fitness system. Journal of Parallel and Distributed Computing, 118, 14–21. https://doi.org/10.1016/j.jpdc.2017.05.006
Ganapathy, V. (2023). AI in auditing: A comprehensive review of applications, benefits and challenges. Shodh Sari-An International Multidisciplinary Journal, 02(4), 328–343. https://doi.org/10.59231/SARI7643
Zheng, X., Le, Y., Chan, A. P. C., Hu, Y., & Li, Y. (2016). Review of the application of social network analysis (SNA) in construction project management research. International Journal of Project Management, 34(7), 1214–1225. https://doi.org/10.1016/j.ijproman.2016.06.005