The Impact of Artificial Intelligence Adoption and Agility on Career performance
DOI:
https://doi.org/10.37641/jimkes.v13i6.4080Keywords:
Agility, Artificial Intelligence, Career Performance, Path Analysis, Work EfficiencyAbstract
The rapid advancement of artificial intelligence in the era of industrial revolution 4.0 has transformed work dynamics globally, yet its impact on individual work efficiency and career performance in developing regions, such as South Sulawesi, remains to be seen. This study investigates the influence of artificial intelligence adoption and agility on employees’ work efficiency and career performance in South Sulawesi. A quantitative approach was employed, involving a survey of 280 respondents from both private and public sectors using a 5-point Likert scale questionnaire. The variables examined were artificial intelligence adoption, agility, work efficiency, and career performance, with data analysed through path analysis using SmartPLS. The findings reveal that artificial intelligence adoption and agility significantly affect both work efficiency and career performance, directly and indirectly, with work efficiency acting as a mediating variable. Artificial intelligence adoption recorded a total effect of 0.406 on career performance, while agility contributed 0.361. Furthermore, work efficiency had a direct effect of 0.273 on career performance, underscoring its vital role in supporting career advancement. The study suggests that organizations should promote AI adoption and enhance employee agility through training and adaptive skill development.
Downloads
References
Adhiatma , A., Fachrunnisa, O., Nurhidayati, & Rahayu, T. (2023). Creating digital ecosystem for small and medium enterprises: the role of dynamic capability, agile leadership and change readiness. Journal of Science and Technology Policy Management, 14(5), 941-959.
Al Naim, A. F. (2023). Enhancing workforce productivity and organizational agility through digital transformation: Role of technological integration, skills development initiatives and low organizational trust. Journal Modern PM, 1(1), 1-14.
Aldoseri, A., Al-Khalifa, K. N., & Hamouda, A. M. (2024). AI-powered innovation in digital transformation: Key pillars and industry impact. Sustainability, 16(5), 1790-1801.
Almosawi, F., Aldoseri, N., & Al-Sartawi, A. (2024). The impact of artificial intelligence accounting systems on workforce productivity and job satisfaction. In Business Analytical Capabilities and Artificial Intelligence-enabled Analytics: Applications and Challenges in the Digital Era, Vol. 2. Cham: Springer Nature Switzerland.
Arntz, M., Gregory, T., & Zierahn, U. (2016). The risk of automation for jobs in OECD countries: A comparative analysis. OECD Social, Employment, and Migration Working Paper, 189(1), 1-35.
Brynjolfsson, E., & Hitt, L. M. (2000). Beyond computation: Information technology, organizational transformation, and business performance. Journal of Economic Perspectives, 14(4), 23-48.
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. New York: W. W. Norton & Company.
Brynjolfsson, E., Rock, D., & Syverson, C. (2017). Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. Retrieved in July 1, 2025 from https://www.nber.org/papers/w24001
Carter, A., & Varney, S. (2018). Change capability in the agile organization. Institute for Employment Studies Member Paper, 139(1), 1-12.
Dalsaniya, A., & Patel, K. (2022). Enhancing process automation with AI: The role of intelligent automation in business efficiency. International Journal of Science and Research Archive, 5(2), 322-337.
Davenport, T. H., & Kirby, J. (2016). Just how smart are smart machines?. MIT Sloan Management Review, 57(3), 21-30.
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerization? Technological Forecasting and Social Change, 11(4), 254-280.
Guruprasad, R., Abood, B. S. Z., Al-Khalidi, A., Abdulhasan, M. M., Thomas, S., & Naqvi, S. R. (2024). Corporate agility and AI: Enhancing adaptive strategies for a dynamic technological landscape. 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2(3), 1090-1094.
Haylemariam, L. G., Oduro, S., & Tegegne, Z. L. (2024). Entrepreneurial agility and organizational performance of IT firms: A mediated moderation model. Journal of Entrepreneurship, Management & Innovation, 20(2), 23-31.
Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586.
Kahya, E. (2009). The effects of job performance on effectiveness. International Journal of Industrial Ergonomics, 39(1), 96-104.
Kaplan, A., & Haenlein, M. (2019). Siri, Siri in my hand, who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15-25.
Kewsuwun, N. (2020). The digital economy: Rethinking promise and peril in the age of networked intelligence (2nd). Journal of Information Science Research and Practice, 38(2), 84-92.
Kim, Y. H., Choe, E. K., Lee, B., & Seo, J. (2019). Understanding personal productivity: How knowledge workers define, evaluate, and reflect on their productivity. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. 2(2), 1-12.
Kumar, D. (2024). AI-driven automation in administrative processes: Enhancing efficiency and accuracy. International Journal of Engineering Science and Humanities, 14(1), 256-265.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. London: Pearson Education.
Makridakis, S. (2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, 9(1), 46-60.
Menon, S., & Suresh, M. (2021). Factors influencing organizational agility in higher education. Benchmarking: An International Journal, 28(1), 307-332.
Mindell, D. A., & Reynolds, E. (2023). The work of the future: Building better jobs in an age of intelligent machines. Cambridge: Mit Press.
Muduli, A., & Choudhury, A. (2024). Digital technology adoption, workforce agility and digital technology outcomes in the context of the banking industry of India. Journal of Science and Technology Policy Management, 4(1), 12-23.
Oktaviani, A. R. (2025). Work agility in the disruptive era: The role of locus of control in female employees of SOEs. Jurnal Ilmiah Manajemen Kesatuan, 13(5), 3713–3724.
Olan, F., Arakpogun, E. O., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business Research, 145(1), 605-615.
Prastyaningtyas, E. W., Ausat, A. M. A., Muhamad, L. F., Wanof, M. I., & Suherlan, S. (2023). The role of information technology in improving human resources career development. Jurnal Teknologi dan Sistem Informasi Bisnis, 5(3), 266-275.
Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). London: Pearson.
Savitha, M., & Kumar, S. P. (2025). Building an agile organizational structure to drive innovation and technology. Cuestiones de Fisioterapia, 54(2), 2321-2334.
Schwab, K. (2017). The fourth industrial revolution. New York: Crown Publishing Group.
Setyawati, N. W., PG, D. S. W., & Rianto, M. R. (2022). Career development, motivation and promotion on employee performance. East Asian Journal of Multidisciplinary Research, 1(9), 1957-1970.
Stone, D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, K. R. (2015). The influence of technology on the future of human resource management. Human Resource Management Review, 25(2), 216-231.
Syamil, A., La Ode, N., Rosariana, B. C., Aristy, L. M., & Liesl, R. (2025). The roles of agility, supply chain sustainability, and risk management on operations performance in manufacturing industry. Jurnal Ilmiah Manajemen Kesatuan, 13(3), 1387–1398.
Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42.
Varshney, K. R., & Alemzadeh, H. (2017). On the safety of machine learning: Cyber-physical systems, decision sciences, and data products. Big Data, 5(3), 246-255.
Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading digital: Turning technology into business transformation. Cambridge, MA: Harvard Business Press.
Yusriadi, Y., Rusnaedi, R., Siregar, N. A., Megawati, S., & Sakkir, G. (2023). Implementation of artificial intelligence in Indonesia. International Journal of Data and Network Science, 7(1), 1-13.
Zhang, W., Guan, X., Zhou, X., & Lu, J. (2019). The effect of career adaptability on career planning in reaction to automation technology. Career Development International, 24(6), 545-559.





