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Artificial Intelligence Models and Employee Lifecycle Management: a Systematic Literature Review

EasyChair Preprint no. 8857

23 pagesDate: September 22, 2022


Background/Purpose: The use of artificial intelligence (AI) models for data-driven decision-making in different stages of employee lifecycle (EL) management is increasing. However, there is no comprehensive study that addresses contributions of AI in EL management. Therefore, the main goal of this study was to address this theoretical gap and determine the contribution of AI models to EL.
Methods: This study applied the PRISMA method, a systematic literature review model, to ensure that the maximum number of publications related to the subject can be accessed. The output of the PRISMA model led to the identification of 23 related articles, and the findings of this study were presented based on the analysis of these articles.
Results: The findings revealed that AL algorithms were used in all stages of EL management (i.e., recruitment, on-boarding, employability and benefits, retention, and off-boarding). It was also disclosed that Random Forest, Support Vector Machines, Adaptive Boosting, Decision Tree, and Artificial Neural Network algorithms outperform other algorithms and were the most used in the literature.
Conclusion: Although the use of AI models in solving EL problems is increasing, research on this topic is still in its infancy stage, and more research on this topic is necessary.

Keyphrases: Artificial Intelligence, deep learning, Employee Lifecycle, Human Resource Management, machine learning, PRISMA, Systematic Literature Review

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Saeed Nosratabadi and Roya Khayer Zahed and Vadim Vitalievich Ponkratov and Evgeniy Vyacheslavovich Kostyrin},
  title = {Artificial Intelligence Models and Employee Lifecycle Management: a Systematic Literature Review},
  howpublished = {EasyChair Preprint no. 8857},

  year = {EasyChair, 2022}}
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