Artificial Intelligence Use, Employee Productivity, and Job Performance: Evidence from a Cross-Sector Survey
DOI:
https://doi.org/10.51325/9r12yc26Keywords:
Artificial Intelligence, Employee Productivity, Job Performance, Workplace Automation, Human-AI Collaboration, Organizational Efficiency, Digital TransformationAbstract
The Artificial Intelligence (AI) has significantly impacted the world of work in terms of automation, decision making, and increased efficiency of employees. This paper focuses on how AI impacts the efficiency of the employees in an organization. The primary goal of this research paper is to investigate the impact of application of AI on efficiency, workload, work speed, and performance of the employees. The research methodology adopted for this paper includes a quantitative approach whereby surveys will be conducted on employees in the Information Technology, Finance, and Services sectors. The variables used in this research are AI usage level, productivity improvement index, performance, and satisfaction of workers. As can be observed from the results, the application of AI technology has significant influence on the productivity of the employees, where productivity scores increased from 2.86 to 4.32 for low and high AI users, respectively, while job performance scores increased from 3.01 to 4.48, respectively. The results of regression analysis show that there is significant positive correlation between the application of AI and efficiency at work (β = 0.54, p < 0.01). Nevertheless, some issues arise with regard to the adaptation of workers to their new skills and over-reliance on automation. However, it should be pointed out that the use of AI has the potential to improve productivity in AI-adopting firms, provided that it is wisely combined with human resources.
References
Abasaheb, S. A., & Subashini, R. (2023). Maneuvering of digital transformation: Role of artificial intelligence in empowering leadership—An empirical overview. International Journal of Professional Business Review, 8(5), Article e01838. https://doi.org/10.26668/businessreview/2023.v8i5.1838 DOI: https://doi.org/10.26668/businessreview/2023.v8i5.1838
Agha, H. N. A., Eyupoglu, S. Z., & Tashtoush, L. (2025). The relationship between human resource management practices and organizational innovation: The mediated role of human capital within the banking sector in North Iraq. Sustainability, 17(14), Article 6330. https://doi.org/10.3390/su17146330 DOI: https://doi.org/10.3390/su17146330
Aly, H. (2022). Digital transformation, development and productivity in developing countries: Is artificial intelligence a curse or a blessing? Review of Economics and Political Science, 7(4), 238–256. https://doi.org/10.1108/REPS-11-2019-0145 DOI: https://doi.org/10.1108/REPS-11-2019-0145
Ateeq, K., Oswal, N., Jawabri, A., Al Masaeid, T., Alquqa, E. K., Basha, S. E., & Alami, R. (2025). The transformative impact of artificial intelligence (AI) on organisational behaviour (OB): A study of employee engagement, performance, and ethical implications. Journal of Posthumanism, 5(4), 1245–1256. https://doi.org/10.63332/joph.v5i4.1221 DOI: https://doi.org/10.63332/joph.v5i4.1221
Baharuddin, A. H. (2026). The role of technology in enhancing HR compliance and workforce management: Implications for organizational agility and employee development. Golden Ratio of Mapping Idea and Literature Format, 6(2), 1604–1614. https://doi.org/10.52970/grmilf.v6i2.2109
Das, S. R., Sarkar, P., Patil, S., Sharma, R., Aggarwal, S., & Lourens, M. (2023). Artificial intelligence in human resource management: Transforming business practices. In 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) (Vol. 10, pp. 1699–1703). IEEE. https://doi.org/10.1109/UPCON59197.2023.10434524 DOI: https://doi.org/10.1109/UPCON59197.2023.10434524
Deepa, B. G., Lakshmi, D. V., Gondkar, S. R., Dandu, R., & Gondkar, R. R. (2025). Investigating the role of intelligent HR systems in enhancing the relationship between employee engagement and performance: A computational perspective for economic development. Indian Journal of Information Sources and Services, 15(3), 362–369. https://doi.org/10.51983/ijiss-2025.IJISS.15.3.41 DOI: https://doi.org/10.51983/ijiss-2025.IJISS.15.3.41
Faisal, R. (2025). Ethical AI integration in education: Policies, challenges, and strategies for bridging digital divides in emerging economies. Crossroads of Social Inquiry, 1(2), 1–18. https://doi.org/10.64851/csi.v1i2.28 DOI: https://doi.org/10.64851/csi.v1i2.28
Jones, M. K., Jones, R. J., Latreille, P. L., & Sloane, P. J. (2009). Training, job satisfaction, and workplace performance in Britain: Evidence from WERS 2004. Labour, 23, 139–175. https://doi.org/10.1111/j.1467-9914.2008.00434.x DOI: https://doi.org/10.1111/j.1467-9914.2008.00434.x
Joshi, A., & Masih, J. (2023). Enhancing employee efficiency and performance in Industry 5.0 organizations through artificial intelligence integration. European Economic Letters, 13(4), 300–315. https://doi.org/10.52783/eel.v13i4.589 DOI: https://doi.org/10.52783/eel.v13i4.589
Milukutu, A., & Siachisa, M. (2023). Assessing the impact of digital transformation on employee performance in the public sector: A case study of Zambia’s Ministry of Health Headquarters (2017–2022). International Journal of Humanities, Social Sciences and Education, 10(9), 118–126. https://doi.org/10.20431/2349-0381.1009013 DOI: https://doi.org/10.20431/2349-0381.1009013
Mohan, J., & Halder, A. K. (2025). Exploring the impact of AI-driven talent management models on employee retention in Indian IT companies. Archives for Technical Sciences, 33(2), 1061–1070. https://doi.org/10.70102/afts.2025.1833.1061 DOI: https://doi.org/10.70102/afts.2025.1833.1061
Morandini, S., Fraboni, F., De Angelis, M., Puzzo, G., Giusino, D., & Pietrantoni, L. (2023). The impact of artificial intelligence on workers’ skills: Upskilling and reskilling in organisations. Informing Science: The International Journal of an Emerging Transdiscipline, 26, 39–68. https://doi.org/10.28945/5078 DOI: https://doi.org/10.28945/5078
Osmundsen, K. S. (2024). Digital transformation from an employee perspective: A literature review. Beta, 38(1), 1–18. https://doi.org/10.18261/beta.38.1.1 DOI: https://doi.org/10.18261/beta.38.1.1
Oyekunle, D., & Boohene, D. (2024). Digital transformation potential: The role of artificial intelligence in business. International Journal of Professional Business Review, 9(3), Article e04499. https://doi.org/10.26668/businessreview/2024.v9i3.4499 DOI: https://doi.org/10.26668/businessreview/2024.v9i3.4499
Popescu Ljungholm, D., & Popescu, V. (2023). Generative artificial intelligence algorithms in talent and performance management, job displacement and creation, and employee productivity and well-being. Contemporary Readings in Law and Social Justice, 15(2), 9–25. https://doi.org/10.22381/CRLSJ15220231 DOI: https://doi.org/10.22381/CRLSJ15220231
Qu, F., Tang, Q., Li, C.-M., & Liu, J. (2025). Exploring the impact of digital transformation on productivity: The role of artificial intelligence technology, green technology, and energy technology. Technological and Economic Development of Economy, 31(5), 1499–1530. https://doi.org/10.3846/tede.2025.23009 DOI: https://doi.org/10.3846/tede.2025.23009
Saifi, H., & Saifi, F. (2025). Digital transformation as a socio-economic challenge: The impact on the commercial bank employees’ job performance. SocioEconomic Challenges, 9(3), 48–63. https://doi.org/10.61093/sec.9(3).48-63.2025 DOI: https://doi.org/10.61093/sec.9(3).48-63.2025
Tokunova, A., Zvonar, V., Polozhentsev, D., Pavlova, V., & Fedoruk, O. (2024). Economic consequences of artificial intelligence and labor automation: Employment recovery, transformation of labor markets, and dynamics of social structure in the context of digital transformation. WSEAS Transactions on Financial Engineering, 2, 1–12. https://doi.org/10.37394/232032.2024.2.1 DOI: https://doi.org/10.37394/232032.2024.2.1
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Adnan Jawabri, Raghda Abbas, Rouhi Faisal (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
