THE USE OF ARTIFICIAL INTELLIGENCE IN PEOPLE MANAGEMENT: A BIBLIOMETRIC ANALYSIS

Abstract

This article explores the impact and applications of Artificial Intelligence (AI) in people management, with a focus on bibliometric analysis. AI has revolutionized various sectors, including Human Resources (HR), where it has enabled the automation of processes, making them more agile and precise.

Introduction

Artificial Intelligence has enabled the automation of processes in the area of people management, making them more agile, facilitating the execution of repetitive tasks, the creation of more accurate and useful reports for other departments, and reducing rework.

Applications of AI in People Management

AI can be applied in people management through Biometrics, where the company has control over the entry and exit of employees, favoring the calculation of hours worked. In addition, AI emerges as a tool to facilitate the analysis of data generated by the organization itself, as well as to assist in decision-making by senior management.

Bibliometric Analysis

Bibliometric analysis is a quantitative and statistical technique that allows assessing the impact and relevance of a field of study. In this case, it will be applied to assess the extent of the use of AI in people management.

Bibliometric Metrics

Bibliometric metrics are valuable tools for evaluating scientific production and the interactions between its elements. Some of the main metrics used include Impact Factor, h-index, Alternative Metrics, Citations per Article, Journal Citation Rate, Degree of Collaboration among Authors, Citation and Co-citation Analysis, Word and Phrase Analysis, and Growth of Specific Areas.

Limitations of Bibliometric Metrics

Despite their usefulness, bibliometric metrics have some significant limitations. They vary by area of knowledge, document type, and focus on quantity, not quality. In addition, they can be influenced by various factors, such as the area of research and language.

Mitigation of Limitations

To mitigate these limitations, it is important to use a combination of different metrics, consider the context when interpreting the metrics, use qualitative evaluations along with bibliometric metrics, be aware that metrics can be manipulated, and regularly update your analyses.

Conclusion

AI has the potential to transform people management, making processes more efficient and precise. However, it is important that organizations are aware of the ethical and legal implications of using AI.

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