Artificial Intelligence and Its Impact on Economic Growth
Choudhary, Sanju
Assistant Professor in Computer Science, F.G.M. Govt. College, Adampur (Hisar), Haryana
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.
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