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The chapter references technological applications' advancements in the HRM function and suggests the revised HRM function in Industry 5.0. In the first part, a brief background has been given on the technological advancements in the function followed by an extensive literature review of the ongoing and probable application areas of technologies in HRM function. Subsequently, the author develops certain models of operations that the HRs will have to follow, which will help in imbibing the technological practices of machine learning, artificial intelligence, blockchain while adhering to the data privacy practices. Thus, this approach makes the HRM function more automated but vigilant and strategic simultaneously so that HRs can monitor and control the cobots in Industry 5.0.

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This is a review paper of the different predictive models which have been developed for determining employee attrition and it also provides a strategic guideline that the human resource management team can consider implementing in the wake of digital disruption. In the first half of the paper, the introduction to predictive models of attrition has been discussed about the methodology used to refer to the different journal databases and years of publication along with the key variables that have been used. In the discussion section, the gaps have been identified as to why the existing models fail to establish the exact reasons and ascertain the level of attrition properly especially as we see in the case of the massive resignations that are taking place in the workplace through a set of questions which identify the specific areas, yet to be considered in the models. Finally, based on the review, the hybrid conceptual framework has been developed to provide a direction in the future as to how organizations can consider breaking down their structure and in turn capture their emotions and data and finally apply it to determine the reasons and levels of employee attrition.