The Use of Artificial Intelligence in Personnel Management

DOI

10.2991/aebmr.k.200502.025How to use a DOI?

Keywords

personnel, HR-specialist, recruiter, competency model, job profile, artificial intelligence, chat bots

Abstract

The modern concept of enterprise management involves the separation from a large number of functional areas of managerial activity of the one that is associated with the management of the personnel component of production - the enterprise staff. Global technological and structural changes, increasing competition, the globalization of production, the development of international relations, cooperation and integration, make it increasingly difficult to manage this critical area of management. In these conditions, in many modern enterprises, human resources specialists have begun to actively use intelligent technologies to help recruiters in much shorter terms and more efficiently solve tasks such as recruitment and placement of personnel, staff training, its adaptation and assessment of work, etc. The main advantages and benefits, as well as the risks that artificial intelligence carries in the process of application in personnel management. The paper provides a comparative analysis of the use of artificial intelligence by foreign and Russian companies. The main achievements and problems in this area by domestic enterprises are identified. The study also led to the conclusion that there is a direct link between the use of artificial intelligence and the level of development of companies.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - E.O. Tappaskhanova
AU  - Z.A. Mustafaeva
AU  - R. A. Tokmakova
PY  - 2020
DA  - 2020/05/05
TI  - The Use of Artificial Intelligence in Personnel Management
BT  - Proceedings of the 2nd International Scientific and Practical Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth” (MTDE 2020)
PB  - Atlantis Press
SP  - 157
EP  - 163
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.200502.025
DO  - 10.2991/aebmr.k.200502.025
ID  - Tappaskhanova2020
ER  -