Predictive Maintenance of personnel turnover in Microenterprises with AI
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Abstract
In the current context, characterized by competitiveness in the field of microenterprises and the growing demand in the management of human talent, there has been a notable boost towards the incorporation of Artificial Intelligence (AI) in these organizations. A crucial aspect that stands out is the insufficiency of effective strategies to anticipate and mitigate employee turnover, which has become one of the primary approaches. The purpose of this article is to identify factors that influence the preventive maintenance of unnecessary employee turnovers and improve the area of human talent with AI. A systematic review of 247 articles was conducted, which were selected based on a search in high-impact databases such as Scopus, SpringerLink and Wef of Science, using inclusion and exclusion criteria. Three search questions were used, and the use of Excel software to perform a content analysis, through PRISMA coding. As a result, talent management and the use of artificial intelligence will allow identifying factors to prevent staff turnover. Finally, the human talent area faces challenges in the implementation of preventive maintenance of rotation and that can be overcome with AI in microenterprises, improving operational efficiency and operational sustainability.
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