Empirical Insights Into AI Personalization’s Role in Enhancing Employee Retention Amid Privacy Challenge

Abstract

The development of Artificial Intelligence (AI) transforms the dynamics of workforce following the increase of remote working in the aftermath of the pandemic. Operational efficiency, workforce experience and retention are yet to be established conclusively. These are some of the questions that AI-based personalisation offers. Nonetheless, the privacy and the trust are put at stake with this AI personalization. The given study is the first one to develop an integrated framework that includes Protection Motivation Theory (PMT), Unified Theory of Acceptance and Use of Technology (UTAUT2), and Self-Determination Theory (SDT) to examine the effects of AI-personalization on the engagement of employees, their willingness to change, and retention. It includes privacy concern as a moderating variable, which makes it relevant to an organization and expands the existing discussions that were confined to the consumer setting. Based on Survey information of 322 out of 463 professionals in India who are currently on remote working. Smart PLS4 assists in the analysis of the current study using SEM-PLS. The outcome and the findings reveal that there is a direct hypothesis support and it also indicates a new, multi-level based framework of comprehending AI integration and retention that could be utilized in global workforce management. Practical implications of the study state that it is not merely the application of AI personalization to the workforce, but it also requires considering the issue of privacy to maintain the trust of the employees, and it will lead to retaining the talent of the organization.