The Impact of Artificial Intelligence on Job Performance: A Systematic Review

https://doi.org/10.51867/ajernet.7.1.11

Auteurs

Mots-clés :

Artificial intelligence, Bibliometric Analysis, Job Performance, VOSviewer

Résumé

The rapid diffusion of artificial intelligence (AI) technologies across organizational functions has intensified scholarly interest in their implications for employee job performance. While existing studies highlight both productivity gains and emerging challenges associated with AI adoption, the intellectual structure, thematic evolution, and research frontiers of this growing body of literature remain fragmented. The goal of this study is to organize the scholarly contribution to the impact of artificial intelligence on job performance. The study was carried out by examining 1,747 publications that were indexed in the Scopus database. The data were analyzed to give an overview of the domain using the PRISMA sampling approach and VOSviewer software. We then reported tables, graphs, and maps to highlight the key performance metrics for the creation of articles and their citations. The findings demonstrate the frequent usage of phrases like “job performance,” “artificial intelligence,” “organization performance,” “human resources management,” “performance management,” and “machine learning,” among others. Furthermore, some of the more recent study subjects are revealed by the density map, including “digital education technology,” “innovation performance,” “emotional intelligence,” “big data analysis,” “deep learning algorithms,” “data augmentation,” “smart technologies,” and “knowledge specificity." The study offers valuable insights for managers and policymakers who aim to utilize AI to improve job performance while minimizing negative impacts on employees.

Dimensions

Abraham, M., Niessen, C., Schnabel, C., Lorek, K., Grimm, V., Möslein, K., & Wrede, M. (2019). Electronic monitoring at work: The role of attitudes, functions, and perceived control for the acceptance of tracking technologies. Human Resource Management Journal, 29(4), 657-675. https://doi.org/10.1111/1748-8583.12250 DOI: https://doi.org/10.1111/1748-8583.12250

Ali-Hassan, H., Nevo, D., & Wade, M. (2015). Linking dimensions of social media use to job performance: The role of social capital. Journal of Strategic Information Systems, 24(2), 65-89. https://doi.org/10.1016/j.jsis.2015.03.001 DOI: https://doi.org/10.1016/j.jsis.2015.03.001

Ancarani, A., Di Mauro, C., & Mascali, F. (2019). Backshoring strategy and the adoption of Industry 4.0: Evidence from Europe. Journal of World Business, 54(4), 360-371. https://doi.org/10.1016/j.jwb.2019.04.003 DOI: https://doi.org/10.1016/j.jwb.2019.04.003

Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers in Human Behavior, 85, 183-189. https://doi.org/10.1016/j.chb.2018.03.051 DOI: https://doi.org/10.1016/j.chb.2018.03.051

Archambault, É., Campbell, D., Gingras, Y., & Larivière, V. (2009). Comparing bibliometric statistics obtained from the web of science and Scopus. Journal of the American Society for Information Science and Technology, 60(7), 1320-1326. https://doi.org/10.1002/asi.21062 DOI: https://doi.org/10.1002/asi.21062

Benziane, R., Roqiya, S., & Houcine, M. (2022). Fintech Startup: A bibliometric analysis and network visualization. International Journal of Accounting & Finance Review, 11(1), 8-23. https://doi.org/10.46281/ijafr.v11i1.1715 DOI: https://doi.org/10.46281/ijafr.v11i1.1715

Bondarouk, T., & Brewster, C. (2016). Conceptualising the future of HRM and technology research. International Journal of Human Resource Management, 27(21), 2652-2671. https://doi.org/10.1080/09585192.2016.1232296 DOI: https://doi.org/10.1080/09585192.2016.1232296

Bondarouk, T., Harms, R., & Lepak, D. (2015). Does e-HRM lead to better HRM service? International Journal of Human Resource Management, 28(9), 1332-1362. https://doi.org/10.1080/09585192.2015.1118139 DOI: https://doi.org/10.1080/09585192.2015.1118139

Bondarouk, T., Parry, E., & Furtmueller, E. (2016). Electronic HRM: Four decades of research on adoption and consequences. International Journal of Human Resource Management, 28(1), 98-131. https://doi.org/10.1080/09585192.2016.1245672 DOI: https://doi.org/10.1080/09585192.2016.1245672

Buckley, P., Minette, K., Joy, D., & Michaels, J. (2004). The use of an automated employment recruiting and screening system for temporary professional employees: A case study. Human Resource Management, 43(2-3), 233-241. https://doi.org/10.1002/hrm.20017 DOI: https://doi.org/10.1002/hrm.20017

Chow, H. K. H., Choy, K. L., Lee, W. B., & Lau, K. C. (2006). Design of a RFID case-based resource management system for warehouse operations. Expert Systems with Applications, 30(4), 561-576. https://doi.org/10.1016/j.eswa.2005.07.023 DOI: https://doi.org/10.1016/j.eswa.2005.07.023

Colbert, A., Yee, N., & George, G. (2016). The digital workforce and the workplace of the future. Academy of Management Journal, 59(3), 731-739. https://doi.org/10.5465/amj.2016.4003 DOI: https://doi.org/10.5465/amj.2016.4003

Cooke, F. L., Liu, M., Liu, L. A., & Chen, C. C. (2019). Human resource management and industrial relations in multinational corporations in and from China: Challenges and new insights. Human Resource Management, 58(5), 455-471. https://doi.org/10.1002/hrm.21986 DOI: https://doi.org/10.1002/hrm.21986

Crossan, M. M., & Apaydin, M. (2010). A multi-dimensional framework of organizational innovation: A systematic review of the literature. Journal of Management Studies, 47(6), 1154-1191. https://doi.org/10.1111/j.1467-6486.2009.00880.x DOI: https://doi.org/10.1111/j.1467-6486.2009.00880.x

Dulebohn, J. H., & Hoch, J. E. (2017). Virtual teams in organizations. Human Resource Management Review, 27(4), 569-574. https://doi.org/10.1016/j.hrmr.2016.12.004 DOI: https://doi.org/10.1016/j.hrmr.2016.12.004

Fleming, P. (2019). Robots and organization studies: Why robots might not want to steal your job. Organization Studies, 40(1), 23-38. https://doi.org/10.1177/0170840618765568 DOI: https://doi.org/10.1177/0170840618765568

Garcia-Arroyo, J., & Osca, A. (2021). Big data contributions to human resource management: A systematic review. International Journal of Human Resource Management, 32(20), 4337-4362. https://doi.org/10.1080/09585192.2019.1674357 DOI: https://doi.org/10.1080/09585192.2019.1674357

Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in Human Behavior, 97, 304-316. https://doi.org/10.1016/j.chb.2019.01.020 DOI: https://doi.org/10.1016/j.chb.2019.01.020

Hallinger, P., & Kovačević, J. (2019). A bibliometric review of research on educational administration: Science mapping the literature, 1960 to 2018. Review of Educational Research, 89(3), 335-369. https://doi.org/10.3102/0034654319830380 DOI: https://doi.org/10.3102/0034654319830380

Hallinger, P., & Nguyen, V. T. (2020). Mapping the landscape and structure of research on education for sustainable development: A bibliometric review. Sustainability, 12(5), Article 51947. https://doi.org/10.3390/su12051947 DOI: https://doi.org/10.3390/su12051947

Koo, B., Curtis, C., & Ryan, B. (2021). Examining the impact of artificial intelligence on hotel employees through job insecurity perspectives. International Journal of Hospitality Management, Article 102763. https://doi.org/10.1016/j.ijhm.2020.102763 DOI: https://doi.org/10.1016/j.ijhm.2020.102763

Landers, R. N., Bauer, K. N., & Callan, R. C. (2015). Gamification of task performance with leaderboards: A goal setting experiment. Computers in Human Behavior, (August), 1-8. https://doi.org/10.1016/j.chb.2015.08.008 DOI: https://doi.org/10.1016/j.chb.2015.08.008

Larivière, B., Bowen, D., Andreassen, T. W., Kunz, W., Sirianni, N. J., Voss, C., Wünderlich, N. V., & De Keyser, A. (2017). "Service Encounter 2.0": An investigation into the roles of technology, employees and customers. Journal of Business Research, 79, 238-246. https://doi.org/10.1016/j.jbusres.2017.03.008 DOI: https://doi.org/10.1016/j.jbusres.2017.03.008

Loebbecke, C., & Picot, A. (2015). Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda. Journal of Strategic Information Systems, 24(3), 149-157. https://doi.org/10.1016/j.jsis.2015.08.002 DOI: https://doi.org/10.1016/j.jsis.2015.08.002

Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science, 38(6), 937-947. https://doi.org/10.1287/mksc.2019.1192 DOI: https://doi.org/10.1287/mksc.2019.1192

Makanthi, S. P. S., & Hussain, M. A. M. (2016). Impact of job design on employees' performance in People's Banks of. In 5th Annual International Research Conference-2016 (pp. 269-275).

Marler, J. H., & Parry, E. (2016). Human resource management, strategic involvement and e-HRM technology. International Journal of Human Resource Management, 27(19), 2233-2253. https://doi.org/10.1080/09585192.2015.1091980 DOI: https://doi.org/10.1080/09585192.2015.1091980

Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), Article 103434. https://doi.org/10.1016/j.im.2021.103434 DOI: https://doi.org/10.1016/j.im.2021.103434

Moher, D., Liberati, A., & Tetzlaff, J. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ, 2535(July), 1-8. https://doi.org/10.1136/bmj.b2535 DOI: https://doi.org/10.1136/bmj.b2535

Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: Annals of Internal Medicine. Annals of Internal Medicine, 151(4), 264-269. https://doi.org/10.7326/0003-4819-151-4-200908180-00135 DOI: https://doi.org/10.7326/0003-4819-151-4-200908180-00135

Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 126(6), 5113-5142. https://doi.org/10.1007/s11192-021-03948-5 DOI: https://doi.org/10.1007/s11192-021-03948-5

Nerur, S. P., Rasheed, A. A., & Natarajan, V. (2008). The intellectual structure of the strategic management field: An author co-citation analysis. Strategic Management Journal, 29(3), 319-336. https://doi.org/10.1002/smj.659 DOI: https://doi.org/10.1002/smj.659

Newell, S., & Marabelli, M. (2015). Strategic opportunities (and challenges) of algorithmic decision-making: A call for action on the long-term societal effects of "datification." Journal of Strategic Information Systems, 24(1), 3-14. https://doi.org/10.1016/j.jsis.2015.02.001 DOI: https://doi.org/10.1016/j.jsis.2015.02.001

Nyabakora, W. I. (2023a). Earnings management in public companies: A bibliometric review. SN Business & Economics, 3(166), 1-23. https://doi.org/10.1007/s43546-023-00546-w DOI: https://doi.org/10.1007/s43546-023-00546-w

Nyabakora, W. I. (2023b). Virtual environments' knowledge base: A bibliometric analysis. Scientific Visualization, 15(4), 140-158. https://doi.org/10.26583/sv.15.4.11 DOI: https://doi.org/10.26583/sv.15.4.11

Nyabakora, W. I. (2024). The contribution of family businesses to economic growth: A bibliometric review. SAGE Open, 1-16. https://doi.org/10.1177/21582440241301423 DOI: https://doi.org/10.1177/21582440241301423

Park, R. (2016). The roles of OCB and automation in the relationship between job autonomy and organizational performance: A moderated mediation model. International Journal of Human Resource Management, 29(6), 1139-1156. https://doi.org/10.1080/09585192.2016.1180315 DOI: https://doi.org/10.1080/09585192.2016.1180315

Parry, E., & Tyson, S. (2008). Recruitment methods in the UK. Human Resource Management Journal, 18(3), 257-274. https://doi.org/10.1111/j.1748-8583.2008.00070.x DOI: https://doi.org/10.1111/j.1748-8583.2008.00070.x

Parry, E., & Tyson, S. (2011). Desired goals and actual outcomes of e-HRM. Human Resource Management Journal, 21(3), 335-354. https://doi.org/10.1111/j.1748-8583.2010.00149.x DOI: https://doi.org/10.1111/j.1748-8583.2010.00149.x

Pellas, N. (2014). The influence of computer self-efficacy, metacognitive self-regulation and self-esteem on student engagement in online learning programs: Evidence from the virtual world of Second Life. Computers in Human Behavior, 35, 157-170. https://doi.org/10.1016/j.chb.2014.02.048 DOI: https://doi.org/10.1016/j.chb.2014.02.048

Pisani, N. (2009). International management research: Investigating its recent diffusion in top management journals. Journal of Management, 35(2), 199-218. https://doi.org/10.1177/0149206308321552 DOI: https://doi.org/10.1177/0149206308321552

Pisani, N., Kourula, A., Kolk, A., & Meijer, R. (2017). How global is international CSR research? Insights and recommendations from a systematic review. Journal of World Business, 52(5), 591-614. https://doi.org/10.1016/j.jwb.2017.05.003 DOI: https://doi.org/10.1016/j.jwb.2017.05.003

Priyan, P. K., Nyabakora, W. I., & Rwezimula, G. (2023a). A bibliometric review of the knowledge base on capital structure decisions. Vision, 1-13. https://doi.org/10.1177/09722629221140190 DOI: https://doi.org/10.1177/09722629221140190

Priyan, P. K., Nyabakora, W. I., & Rwezimula, G. (2023b). A bibliometric review of the knowledge base on financial inclusion. SN Business & Economics, 3(58), 1-21. https://doi.org/10.1177/09722629221140190 DOI: https://doi.org/10.1007/s43546-023-00441-4

Ramachandran, K. K., Saleth, A. A., Hawladar, S., Asokk, D., Bhaskar, B., & Pitroda, J. R. (2022). Machine learning and role of artificial intelligence in optimizing work performance and employee behavior. Materials Today: Proceedings, 51, 2327-2331. https://doi.org/10.1016/j.matpr.2021.11.544 DOI: https://doi.org/10.1016/j.matpr.2021.11.544

Said, B., Kustiani, L., & Sumtaky, M. (2022). Analysis of workload, work environment adaptability, and employee performance in the fish safety industry sector. East African Scholars Journal of Economics, Business and Management, 5(10), 317-327.

https://doi.org/10.36349/easjebm.2022.v05i10.008 DOI: https://doi.org/10.36349/easjebm.2022.v05i10.008

Schaubroeck, J. M., & Yu, A. (2017). When does virtuality help or hinder teams? Core team characteristics as contingency factors. Human Resource Management Review, 27(4), 635-647. https://doi.org/10.1016/j.hrmr.2016.12.009 DOI: https://doi.org/10.1016/j.hrmr.2016.12.009

Seeck, H., & Diehl, M. R. (2017). A literature review on HRM and innovation-taking stock and future directions. International Journal of Human Resource Management, 28(6), 913-944. https://doi.org/10.1080/09585192.2016.1143862 DOI: https://doi.org/10.1080/09585192.2016.1143862

Stone, D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, R. (2015). The influence of technology on the future of human resource management. Human Resource Management Review, 25(2), 216-231. https://doi.org/10.1016/j.hrmr.2015.01.002 DOI: https://doi.org/10.1016/j.hrmr.2015.01.002

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207-222. https://doi.org/10.1111/1467-8551.00375 DOI: https://doi.org/10.1111/1467-8551.00375

Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2021). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. International Journal of Human Resource Management, 33(6), 1237-1266. https://doi.org/10.1080/09585192.2020.1871398 DOI: https://doi.org/10.1080/09585192.2020.1871398

Wang, Z., & Zou, D. (2021). Synchronous computer mediated communication in English language classes during the pandemic: A case study of Wuhan. In Lecture Notes in Computer Science (Vol. 13089, pp. 325-333). https://doi.org/10.1007/978-3-030-92836-0_28 DOI: https://doi.org/10.1007/978-3-030-92836-0_28

Zanko, M., Badham, R., Couchman, P., & Schubert, M. (2008). Innovation and HRM: Absences and politics. International Journal of Human Resource Management, 19(4), 562-581. https://doi.org/10.1080/09585190801953616 DOI: https://doi.org/10.1080/09585190801953616

Publiée

2026-01-13

Comment citer

Yusuph, M. L., Kisumbe, L. A., & Kasubi, J. W. (2026). The Impact of Artificial Intelligence on Job Performance: A Systematic Review. African Journal of Empirical Research, 7(1), 132–150. https://doi.org/10.51867/ajernet.7.1.11

Numéro

Vol. 7 No 1 (2026): Jan-Mar 2026

Rubrique

Articles
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(c) Tous droits réservés Mashala L. Yusuph, Lazaro A. Kisumbe, John W. Kasubi 2026

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Ce travail est disponible sous licence Creative Commons Attribution - Pas d’Utilisation Commerciale 4.0 International.

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