Systematic Literature Review on the Relationship between Employee Engagement and Artificial Intelligence

Authors

  • Rahul Bhattacharyya Author
  • Dr. Roshni James Author

DOI:

https://doi.org/10.53555/jaes.v22i1.123

Keywords:

Artificial Intelligence, Employee Engagement, Human Resources

Abstract

This paper is a Systematic Literature Review (SLR) where we look at the complex relationship between Employee Engagement (EE) and Artificial Intelligence (AI), specifically Generative AI (GenAI) and the objectives. In this review, the study has examined 133 scholarly works, including studies based on experiments and concepts, to come up with the dynamic research landscape in this field. Outcomes indicate a steep increase in the field of research on relationship between Artificial Intelligence and Human Resource from 2016, with a significant increase on research in this area after the COVID-19 pandemic. This literature review is based on the Job Demands–Resources (JD-R) framework, analysing the increase in engagement, productivity, and satisfaction, by increasing efficiency and GenAI adoption as job resources. In parallel we also look at AI-induced technostress as a job demand that contributes to exhaustion and work–life imbalance. This study looks at how the evolution of Generative AI has helped in transforming the impression of HR from being administrative to more strategic by automating repetitive tasks, facilitating HR professionals focus on engagement of employees and building organizational culture. Employee Experience has increased over time and sustained engagement have been reinforced by useful applications of AI in areas like predictive analytics for attrition forecasting, structured learning programs and instantaneous feedback mechanisms. This review also emphasises current ethical challenges like reduction in algorithmic bias, maintenance of data transparency and privacy, and addressing employee anxieties regarding job security and trust thereby ensuring a human touch in deployment.

 

Author Biographies

  • Rahul Bhattacharyya

    Research Scholar, Xavier Institute of Management and Entrepreneurship, Bangalore (A Research Centre affiliated to the University of Mysore), Karnataka, India

  • Dr. Roshni James

    Director, Xavier Institute of Management and Entrepreneurship, Bangalore (A Research Centre affiliated to the University of Mysore), Karnataka, India

References

1. Albaroudi, E., Mansouri, T., and Alameer, A. (2024). A comprehensive review of AI techniques for addressing algorithmic bias in job hiring. AI (Basel, Switzerland), 5(1). https://doi.org/10.3390/ai5010019

2. Ala-Luopa, S., Olsson, T., Väänänen, K., Hartikainen, M., and Makkonen, J. (2024). Trusting intelligent automation in expert work: Accounting practitioners’ experiences and perceptions. Computer Supported Cooperative Work, 33(4). https://doi.org/10.1007/s10606-024-09499-6

3. Ali, N. A., and Somu, S. (2023). Revolutionizing employee engagement measurement: A sentiment analysis framework based on the five ‘V’ elements. In S. Sarma, S. Narang, and K. Prity (Eds.), The adoption and effect of artificial intelligence on human resources management, Part A . Emerald Publishing Limited.

4. Ammirato, S., Felicetti, A. M., Troise, C., and Corvello, V. (2024). Human resources well-being in innovative start-ups: Insights from a systematic review of the literature. Journal of Innovation and Knowledge, 9(4). https://doi.org/10.1016/j.jik.2024.100580

5. Aramali, V., Cho, N., Pande, F., Al-Mhdawi, M. K. S., Ojiako, U., and Qazi, A. (2025). Generative AI in project management: Impacts on corporate values, employee perceptions, and organizational practices. Project Leadership and Society. https://doi.org/10.1016/j.plas.2025.100191

6. Arora, R., and Damarla, R. B. (2025). A review on generative AI powered talent management, employee engagement and retention strategies: Applications, benefits, and challenges. Procedia Computer Science. https://doi.org/10.1016/j.procs.2025.03.247

7. Arslan, A., Cooper, C., Khan, Z., Golgeci, I., and Ali, I. (2021). Artificial intelligence and human workers interaction at team level: A conceptual assessment of the challenges and potential HRM strategies. International Journal of Manpower. https://doi.org/10.1108/IJM-01-2021-0052

8. Bakker, A. B., and Demerouti, E. (2007). The job demands-resources model: State of the art. Journal of Managerial Psychology. https://doi.org/10.1108/02683940710733115

9. Balasubramaniam, N., Krivtsova, E., Lwakatare, L. E., Munezero, M., and Al-Hamadi, H. (2023). Transparency and explainability of AI systems: From ethical guidelines to requirements. Information and Software Technology. https://doi.org/10.1016/j.infsof.2023.107197

10. Bastida, M., Vaquero García, A., Vazquez Taín, M. Á., and Del Río Araujo, M. (2025). From automation to augmentation: Human resource's journey with artificial intelligence. Journal of Industrial Information Integration. https://doi.org/10.1016/j.jii.2024.100872

11. Bositkhanova, N., and Dadaboyev, S. M. U. (2025). The utilization of AI in workforce planning: A systematic literature review. Discover Global Society. https://doi.org/10.1007/s44282-025-00252-y

12. Boudarbat, B., and Montmarquette, C. (2023). AI and employee development: Transforming learning and career planning. Journal of Career Assessment.

13. Burnett, J. R., and Lisk, T. C. (2019). The future of employee engagement: Real-time monitoring and digital tools for engaging a workforce. International Studies of Management and Organization. https://doi.org/10.1080/00208825.2019.1565097

14. Chuang, Y.-T., Chiang, H.-L., and Lin, A.-P. (2025). Insights from the Job Demands–Resources Model: AI’s dual impact on employees’ work and life well-being. International Journal of Information Management. https://doi.org/10.1016/j.ijinfomgt.2025.102887

15. Dadd, D., and Hinton, M. (n.d.). Performance measurement and evaluation: Applying return on investment (ROI) to human capital investments.

16. Danner, M., Hadžić, B., Weber, T., Zhu, X., and Rätsch, M. (2023). Towards equitable AI in HR: Designing a fair, reliable, and transparent human resource management application. In International Conference on Deep Learning Theory and Applications. Springer.

17. Dinesh Kannaa, K. V., and Karthika, S. (2024). AI and automation in human resources. International Journal of Research in Human Resource Management. https://doi.org/10.33545/26633213.2024.v6.i2e.244

18. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., and Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2021.04.070

19. Garg, R., Kiwelekar, A. W., Netak, L. D., and Ghodake, A. (2021). i-Pulse: A NLP based novel approach for employee engagement in logistics organization. International Journal of Information Management Data Insights. https://doi.org/10.1016/j.jjimei.2021.100011

20. Gerdiken, E., Reinwald, M., and Kunze, F. (2021). Outcomes of technostress at work: A meta-analysis. Academy of Management Proceedings, 2021(1). https://doi.org/10.5465/ambpp.2021.11807abstract

21. Glikson, E., and Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals. https://doi.org/10.5465/annals.2018.0057

22. Gómez Gandía, J. A., de Lucas Ancillo, A., and del Val Núñez, M. T. (2025). Knowledge and artificial intelligence on employee behaviour advancing safe and respectful workplace. Journal of Innovation and Knowledge. https://doi.org/10.1016/j.jik.2024.100750

23. Hariri, W. (2023). Unlocking the potential of ChatGPT: A comprehensive exploration of its applications, advantages, limitations, and future directions in natural language processing. arXiv. http://arxiv.org/abs/2304.02017.arXiv

24. Hinge, P., Thakur, A., and Salunkhe, H. (2023). Analysis of human resources attrition: A thematic and sentiment analysis approach. Applications of Machine Intelligence and Data Analytics. https://doi.org/10.2991/978-94-6463-136-4_72

25. Kahn, W. A. (1990). Psychological conditions of personal engagement and disengagement at work. Academy of Management Journal. https://doi.org/10.2307/256287

26. Katam, R. (2024). Data + AI driven solutions for enhancing employee wellbeing and work-life balance. Interantional Journal of Scientific Research in Engineering and Management, 8.

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

28. Krakowski, S. (2025). Human-AI agency in the age of generative AI. Information and Organization. https://doi.org/10.1016/j.infoandorg.2025.100560

29. Malik, A., Budhwar, P., Mohan, H., and NR, S. (2023). Employee experience–the missing link for engaging employees: Insights from an MNE’s AI-based HR ecosystem. Human Resource Management. https://doi.org/10.1002/hrm.22133

30. Marr, B. (2023). The future of work: How AI and technology are shaping the workplace. Forbes.

31. Mer, A., and Srivastava, A. (2023). Employee engagement in the new normal: Artificial intelligence as a buzzword or a game changer? In P. Tyagi, N. Chilamkurti, S. Grima, K. Sood, and B. Balusamy (Eds.), The adoption and effect of artificial intelligence on human resources management, Part A. Emerald Publishing Limited. https://doi.org/10.1108/978-1-80382-027-920231002

32. Mirtaheri, S. L., Movahed, N., Shahbazian, R., Pascucci, V., and Pugliese, A. (2026). Cybersecurity in the age of generative AI: A systematic taxonomy of AI-powered vulnerability assessment and risk management. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2025.108107

33. Nayak, R. L. (2024). Navigating the AI revolution in HRM: A sentiment analysis perspective. Educational Administration: Theory and Practice.

34. Noerman, T., Riyadi, E. S., Yuliaji, E. S., and Natasha, C. A. M. (2025). The impacts of social influence and hedonic motivation on experience and continuance intention of using AI in SMEs’ HRM. Cogent Business and Management. https://doi.org/10.1080/23311975.2025.2542422

35. Obi, L. I., Osuizugbo, I. C., and Awuzie, B. O. (2025). Closing the artificial intelligence skills gap in construction: Competency insights from a systematic review. Results in Engineering. https://doi.org/10.1016/j.rineng.2025.106406

36. Ossiannilsson, E., Altinay, F., Shadiev, R., Benachour, P., Berigel, M., Dagli, G., Ayaz, A., Yikici, B., and Altinay, Z. (2024). Exploring the intersection of artificial intelligence and human resource management: A bibliometric study. Broad Research in Artificial Intelligence and Neuroscience.

37. Pan, Y., and Froese, F. J. (2023). An interdisciplinary review of AI and HRM: Challenges and future directions. Human Resource Management Review. https://doi.org/10.1016/j.hrmr.2022.100924

38. Prentice, C., Wong, I. A., and Lin, Z. (2023). Artificial intelligence as a boundary-crossing object for employee engagement and performance. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2023.103376

39. Rahim, S., Sahar, G., Jabeen, G., Khatoon, S., and Angaiz, D. (2025). Harnessing generative AI: Reviewing applications, challenges, and solutions for out-of-school children in developing regions. Sustainable Futures. https://doi.org/10.1016/j.sftr.2025.101206

40. Raghunathan, N., and Saravanakumar, K. (2023). Challenges and issues in sentiment analysis: A comprehensive survey. IEEE Access. https://doi.org/10.1109/ACCESS.2023.3293041

41. Schaufeli, W. B., Bakker, A. B., and Salanova, M. (2006). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological Measurement. https://doi.org/10.1177/0013164405282471

42. Schaufeli, W. B., Salanova, M., González-Romá, V., and Bakker, A. B. (2002). The measurement of engagement and burnout: A two sample confirmatory factor analytic approach. Journal of Happiness Studies. https://doi.org/10.1023/a:1015630930326

43. Shinde, S. (2025). Predictive HR analytics and employee attrition modelling: A strategic approach to workforce retention in the Indian context. RESEARCH REVIEW International Journal of Multidisciplinary. https://doi.org/10.31305/rrijm.2025.v10.n6.022

44. Shrestha, Y., and Bohr, J. (2024). Enhancing employee experience with AI: Innovations and impacts. Journal of Organizational Behaviour.

45. Sigfrids, A., D'Adda, A., Salini, S., and Oltramari, A. (2023). Human-centricity in AI governance: A systemic approach. Frontiers in Artificial Intelligence, 6. https://doi.org/10.3389/frai.2023.976887

46. Singh, A. P., and Padhi, A. (2025). “Impact of AI and automation on talent acquisition and employee retention.” International Journal of Research Publication and Reviews.

47. Sundari, S., Silalahi, V. A. J. M., Wardani, F. P., Siahaan, R. S., Sacha, S., Krismayanti, Y., and Anjarsari, N. (2024). Artificial Intelligence (AI) and automation in human resources: Shifting the focus from routine tasks to strategic initiatives for improved employee engagement. East Asian Journal of Multidisciplinary Research (EAJMR). https://doi.org/10.55927/eajmr.v3i10.11758

48. Tambe, P., Cappelli, P., and Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review. https://doi.org/10.1177/0008125619867910

49. Tursunbayeva, A. (2024). Artificial intelligence and human resource management. Augmenting human resource management with artificial intelligence: Towards an inclusive, sustainable, and responsible future. Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-75266-7_1

50. Úbeda-García, M., Marco-Lajara, B., Zaragoza-Sáez, P. C., and Poveda-Pareja, E. (2025). Artificial intelligence, knowledge and human resource management: A systematic literature review of theoretical tensions and strategic implications. Journal of Innovation and Knowledge. https://doi.org/10.1016/j.jik.2024.100809

51. Vijai, C. (2023). Artificial intelligence in HR employee experience: Personalization and engagement. In S. Sarma, S. Narang, and K. Prity (Eds.), AI and innovation in HRM: The future of strategic HR in the service economy. (Original work published in The Adoption and Effect of Artificial Intelligence on Human Resources Management, Part A).

52. Virmani, N., Sharma, S., Kumar, P., Luthra, S., Jain, V., and Jagtap, S. (2025). Navigating the landscape through digital human resource management: An initiative to achieve sustainable practices. Sustainable Production and Consumption. https://doi.org/10.1016/j.spc.2024.100621

53. Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., and Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. International Journal of Human Resource Management. https://doi.org/10.1080/09585192.2020.1871398

54. Wang, G., Mansor, Z. D., and Leong, Y. C. (2024). Linking digital leadership and employee digital performance in SMEs in China: The chain-mediating role of high-involvement human resource management practice and employee dynamic capability. Heliyon. https://doi.org/10.1016/j.heliyon.2024.e36026

55. Wang, H., Dang, A., Wu, Z., and Mac, S. (2024). Generative AI in higher education: Seeing ChatGPT through universities' policies, resources, and guidelines. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2024.100326

56. Wassan, S., Ali, Z., and Wassan, S. A. (2021). How artificial intelligence transforms the experience of employees. Türk Bilgisayar Ve Matematik Eğitimi Dergisi. https://doi.org/10.17762/turcomat.v12i10.5603

57. Weng, J., and Aguinis, H. (2024). How to use generative AI as a human resource management assistant. Organizational Dynamics. https://doi.org/10.1016/j.orgdyn.2024.101029

58. Xiao, J., and Yanghong, H. (2024). Architecting the future: Exploring the synergy of AI-driven sustainable HRM, conscientiousness, and employee engagement. Discover Sustainability.

59. Yanamala, K. K. R. (2023). Transparency, privacy, and accountability in AI-enhanced HR processes. Journal of Advanced Computing Systems.

Downloads

Published

2026-01-29

How to Cite

Systematic Literature Review on the Relationship between Employee Engagement and Artificial Intelligence. (2026). Journal of Asia Entrepreneurship and Sustainability, 22(1), 195-204. https://doi.org/10.53555/jaes.v22i1.123