Artificial intelligence between innovation and risks: Its pivotal applications in the industry, healthcare, finance, and agriculture sectors

Authors

Keywords:

agricultural robotics, Artificial intelligence, financial forecasting, healthcare technology, industry 4.0

Abstract

This article aims to highlight the importance of artificial intelligence (AI) and its role in reshaping vital sectors, by focusing on its pivotal applications in industry, healthcare, finance, and agriculture. The main question addressed in this article revolves around the ability of the four sectors to strike a balance between maximizing the benefits of AI’s tremendous innovation and effectively managing its risks and future challenges. The results showed that the four sectors highlighted in this article have benefited from artificial intelligence, The industrial sector witnessed an increase in productivity as a result of the decline in human errors achieved by the automation process. The healthcare sector also benefited from increased efficiency inside operating rooms and improved healthcare. The financial sector also had its share, with complex intelligence applications algorithms providing accurate financial forecasts. Without overlooking the pivotal role played by agricultural robots in increasing agricultural productivity and curbing the escalation of unemployment in rural areas. The study also concluded that the use of artificial intelligence applications poses several risks, such as income inequality and illegal uses, which necessitate the development of fair economic and social policies, and the enactment of strict laws and the development of protection systems.

Downloads

Download data is not yet available.

References

1. Padmaja, C. V. R., Narayana, S. L., Anga, G. L., & Bhansali, P. K. (2024). The rise of artificial intelligence: A concise review. IAES International Journal of Artificial Intelligence, 13(2), 2226–2235. https://doi.org/10.11591/ijai.v13.i2.pp2226-2235.

2. Tay, S. I., Lee, T. C., A. H., N., & Ahmad, A. N. A. (2018). An Overview of Industry 4.0: Definition, Components, and Government Initiatives. Journal of Advanced Research in Dynamical and Control Systems, 10(14-Special Issue), 1378-1387.

3. Ezin, E. C. (2024). Historique et clarifications conceptuelles du Big Data [Technical Report]. ResearchGate. https://doi.org/10.13140/RG.2.2.24400.30726.

4. Fondation de l'Académie des Technologies. (2020). Les robots dans l'industrie : Saisir l'opportunité [Report]. Fondation de l'Académie des Technologies.

5. Qin, J., Liu, Y., & Grosvenor, R. (2016). A categorical framework of manufacturing for Industry 4.0 and beyond. Procedia CIRP, 52, 173–178. https://doi.org/10.1016/j.procir.2016.08.005.

6. Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP, 52, 161–166. https://doi.org/10.1016/j.procir.2016.07.040.

7. TRA-C industrie. (2025). Industrial robotics: challenges and benefits. Retrieved September 30, 2025, from https://www.tra-c.com/fr/ingenierie-industrielle/robotique-industrielle-enjeux-et-interets/

8. International Federation of Robotics. (2024). World Robotics 2024 [Press conference presentation]. International Federation of Robotics.

9. Udegbe, F. C., Ebulue, O. R., Ebulue, C. C., & Ekesiobi, C. S. (2024). The role of Artificial Intelligence in healthcare: A systematic review of applications and challenges. International Medical Science Research Journal, 4(4), 500 508. https://doi.org/10.51594/imsrj.v4i4.1052

10. Quazi, S., Saha, R. P., & Singh, M. K. (2022). Applications of artificial intelligence in healthcare. Journal of Science, Education and Technology, 10(1), 211–226. https://doi.org/10.18006/2022.10(1).211.226.

11. Viswanathan, P. S. (2025). Artificial intelligence in financial services: A comprehensive analysis of transformative technologies and their impact on modern banking. International Journal of Research in Computer Applications and Information Technology (IJRCAIT), 8(1), 336-352. https://doi.org/10.34218/IJRCAIT_08_01_030.

12. Mestiri, S. (2024). Machine learning techniques in financial applications. Journal of Research, Innovation and Technologies, 3(1), 30-40. https://doi.org/10.57017/jorit.v3.1(5).02.

13. Aro, O. E. (2024). Predictive analytics in financial management: Enhancing decision-making and risk management. International Journal of Research Publication and Reviews, 5(10), 2181–2194. https://doi.org/10.55248/genpgi.5.1024.2819.

14. Ashraf, M. (2024). Analyze the impact of artificial intelligence on finance portfolio management. International Journal of Science and Research (IJSR), 13(12), Article SR241211101339. https://doi.org/10.21275/SR241211101339.

15. European Parliament. (2016). EPRS study Research for TRAN Committee: The impact of connected and automated vehicles on the EU transport system (EPRS_STU(2016)581892). European Parliamentary Research Service. https://www.europarl.europa.eu/RegData/etudes/STUD/2016/581892/EPRS_STU(2016)581892_FR.pdf.

16. Aijaz, N., Lan, H., Raza, T., Yaqub, M., Iqbal, R., & Pathan, M. S. (2025). Artificial intelligence in agriculture: Advancing crop productivity and sustainability. Journal of Agriculture and Food Research, 20, 101762. https://doi.org/10.1016/j.jafr.2025.101762.

17. Gangwar, P. (2023, April). Artificial Intelligence in Agriculture. Just Agriculture Newsletter, Vol. 3, Issue 8. https://justagriculture.in/files/newsletter/2023/April/103.%20Artificial%20Intelligence%20in%20Agriculture.pdf.

18. Solos, W. K., & Leonard, J. (2022). On the impact of artificial intelligence on economy. Science Insights, 40(2), 391–400. https://doi.org/10.15354/si.22.re066.

Downloads

Published

24-10-2025

How to Cite

Eddine, A. S. (2025). Artificial intelligence between innovation and risks: Its pivotal applications in the industry, healthcare, finance, and agriculture sectors. The International Tax Journal, 52(5), 2782–2791. Retrieved from https://internationaltaxjournal.online/index.php/itj/article/view/284

Issue

Section

Online Access