Ключевые слова

2304-3369

2308-8842

Вопросы управления

Management issues

10.22394/2304-3369-2025-1-57-79

SLJIHO

Автоматизация управления персоналом: систематический обзор научных публикаций

Personnel Management Automation: systematic scientific publications review

Саматоев

Артем Тимофеевич

Саматоев

Артем Тимофеевич

Samatoev

Artem T.

aptcam90@gmail.com

0009-0009-3941-4925

ООО «УК Полюс» (Москва, Россия) Polyus (Moscow, Russia)

01 01 2025

2025

19 1 57 79 25 09 2024 10 01 2025 29 01 2025

2025

А. Т. Саматоев

A. T. Samatoev

CC BY-NC 4.0

Введение. Автоматизация в области работы с персоналом является одним из способов увеличить эффективность как службы по управлению человеческими ресурсами, так и организации в целом. Целью проведения систематического обзора является анализ развития научной мысли в области автоматизации управления персоналом за последние 5 лет (с 2019 по 2024 годы). Методология и методы. При подготовке обзора учитывались рекомендации PRISMA (2020). В качестве базы данных для анализа использовалась платформа OpenAlex. Поиск осуществлялся по ключевым словам - hr human resources automation, в периметр анализа были включены только научные статьи. В исходную выборку для проведения количественного анализа включены 3727 статьи, при этом учитывались продуктивность авторов статей, использование и взаимосвязь ключевых слов. Для анализа и предоставления результатов использовался пакет bibliometrix для языка программирования R (на основании интерфейса biblioshiny). Для проведения качественного анализа на основании тематического соответствия, содержания и наличия в базе данных Scopus были отобраны 46 работ по 5 основным тематическим направлениям публикаций с наибольшей численностью работ. Доступность отобранных для анализа материалов различается и определяется политикой публикующего журнала/ условиями публикации конкретной статьи. Результаты. Зафиксирован рост количества публикаций по исследуемой теме, выделены наиболее популярные направления исследований: индустрия 4.0 и цифровая трансформация, аналитика в области управления человеческими ресурсами, подходы в области управления персоналом (использование ключевых показателей эффективности, подбор, развитие персонала). Много внимания в рассмотренных работах уделяется потенциалу использования генеративных языковых моделей (подобных ChatGPT) и влиянию автоматизации производственного процесса на работу по управлению персоналом; подчеркивается важность сохранения фокуса на развитии человеческого капитала компаний. Среди сложностей, с которыми приходится сталкиваться организациям, отмечается нехватка профильных компетенций у сотрудников, финансовые издержки при внедрении новых решений и риски нарушения этических норм. Обсуждение. Дальнейшего изучения требует развитие практик управления персоналом под влиянием технологических изменений. В качестве ограничений обзора можно указать возможную неполноту базы данных, использовавшейся для обзора статей, а также субъективность суждений автора в части отбора и проведения качественного анализа статей.

Introduction. Automation in the field of HR is one of the ways to increase both the efficiency of the human resource management service and the organization as a whole. Appropriate reviews of the scientific literature are needed to promote awareness and dissemination of the current technological and management practices application. Companies that use modern technologies gain an advantage that determines their higher level of competitiveness compared to organizations that do not pay enough attention to this area. Technological solutions are developing rapidly, and an overview of innovations and existing trends may be of interest to both researchers and practitioners in the field of personnel management. The purpose of this review is to analyze the scientific thought development in the field of personnel management automation over the past 5 years. This article discusses both the possibilities offered by experts in the field of automation through the implementation of specific technological solutions, and methodological approaches in the field of automation of personnel management. Methodology and methods. The article is a systematic review of scientific publications on the topic of personnel management automation over the past 5 years (since 2019). The OpenAlex platform was used as a database for the analysis. The search date was 23.08.2024, the keywords used were “hr human resources automation”, only scientific articles were included in the analysis perimeter. As a part of the quantitative analysis of the sample, the following items were considered: general characteristics of the sample, productivity of the authors of the articles, an assessment of the use and interrelation of keywords of the sample articles. The bibliometrix package for the R programming language (based on the biblioshiny interface) was used to analyze and present the results. Next, the works were selected for qualitative analysis. Five main thematic areas of publications with the largest number of works were identified. Further, articles were selected out of these works for review based on thematic relevance, content and availability in the Scopus database. The availability of materials selected for analysis varies and is determined by the policy of the publishing journal / publication conditions of a particular article. The PRISMA (2020) recommendations were taken into account when conducting the review. Results. The initial sample for quantitative analysis included 3727 articles, and 46 papers were selected for qualitative analysis. Basing on the analysis, one may conclude that the number of publications on the topic is growing, while the distribution of publication activity by individual authors does not show significant deviations. The most used keywords are directly related to personnel management and digital technologies. Popular areas of work: Industry 4.0 and digital transformation, analysts in the field of human resource management, approaches in the field of personnel management (usage of key performance indicators, recruiting, personnel development, etc.). Conclusions. Much attention in the considered works is paid to the potential of using generative language models (like ChatGPT) and the impact of automation of the production process on the HR function work. Subject matter experts see significant potential in improving HR management processes through the use of modern technological solutions. At the same time, the importance of developing existing practices in the field of human resource management and maintaining a focus on the development of human capital of companies is emphasized. Lack of specialized competencies among employees, financial costs when implementing new solutions and the risks of violating ethical standards are difficulties that organizations may possibly face. The development of personnel management practices under the influence of technological changes requires further study. The main limitations of the review include the possible incompleteness of the database used to review the articles, as well as the risks of the author bias in terms of selecting and conducting a qualitative analysis of the articles. Funding. The review was conducted by the author without any external funding.

Ключевые слова Автоматизация управление персоналом человеческий капитал цифровизация искусственный интеллект

Keywords Automation personnel management human capital digitalization artificial intelligence

Обзор был проведен автором без привлечения внешних источников финансирования.

The review was conducted by the author without any external funding.

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2. Grabowska, S., Saniuk, S., Gajdzik, B. (2022) Industry 5.0: improving humanization and sustainability of Industry 4.0. Scientometrics, 127(6), pp. 3117-3144. DOI 10.1007/s11192-022-04370-1. EDN HBFQRM.

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1. Mishra, S., Ewing, M.T., Cooper, H.B. (2022) Artificial intelligence focus and firm performance. Journal of the Academy of Marketing Science, 50(6), pp. 1176-1197. https://doi.org/10.1007/s11747-022-00876-5. https://elibrary.ru/uyikew.

2. Grabowska, S., Saniuk, S., Gajdzik, B. (2022) Industry 5.0: improving humanization and sustainability of Industry 4.0. Scientometrics, 127(6), pp. 3117-3144. https://doi.org/10.1007/s11192-022-04370-1. https://elibrary.ru/hbfqrm.

3. Proia, S., Carli, R., Cavone, G., Dotoli, M. (2021) Control techniques for safe, ergonomic, and efficient human-robot collaboration in the digital industry: A survey. IEEE Transactions on Automation Science and Engineering, 19(3), pp. 1798-1819. https://doi.org/10.1109/TASE.2021.3131011. https://elibrary.ru/xwivmw.

5. Olsson, A.K., Eriksson, K.M., Carlsson, L. (2025) Management toward Industry 5.0: a co-workership approach on digital transformation for future innovative manufacturing, European Journal of Innovation Management, 28(1), pp. 65-84. https://doi.org/10.1108/EJIM-09-2023-0833.

6. Li, L. (2022) Reskilling and upskilling the future-ready workforce for industry 4.0 and beyond. Information Systems Frontiers, 1-16. https://doi.org/10.1007/s10796-022-10308-y. https://elibrary.ru/mrhorj.

12. Prikshat, V., Malik, A., Budhwar, P. (2023) AI-augmented HRM: Antecedents, assimilation and multilevel consequences. Human Resource Management Review, 33(1), 100860. https://doi.org/10.1016/j.hrmr.2021.100860. https://elibrary.ru/fkojbz.

14. Korzynski, P., Mazurek, G., Altmann, A., Ejdys, J., Kazlauskaite, R., Paliszkiewicz, J., Wach, K., Ziemba, E. (2023) Generative artificial intelligence as a new context for management theories: analysis of ChatGPT. Central European Management Journal, 31(1), 3-13. https://doi.org/10.1108/CEMJ-02-2023-0091. https://elibrary.ru/ghajot.

16. Tanasescu, L.G., Vines, A., Bologa, A.R., Vîrgolici, O. (2024) Data Analytics for optimizing and predicting employee performance. Applied Sciences, 14(8), 3254. https://doi.org/10.3390/app14083254. https://elibrary.ru/nqaldu.

17. Koenig, N., Tonidandel, S., Thompson, I., Albritton, B., Koohifar, F., Yankov, G., Speer, A., Hardy, Ja.H., Gibson, C., Frost, Ch., Liu, M., McNeney, D., Capman, J., Lowery, Sh., Kitching, M., Nimbkar, A., Boyce, A., Sun, T., Guo, F., Min, H. et al. (2023) Improving measurement and prediction in personnel selection through the application of machine learning. Personnel Psychology, 76(4), 1061-1123. https://doi.org/10.1111/peps.12608. https://elibrary.ru/rcugyb.

18. Faqihi, A., Miah, Sh. Ja. (2023) Artificial intelligence-driven talent management system: Exploring the risks and options for constructing a theoretical foundation. Journal of Risk and Financial Management, 16(1), 31. https://doi.org/10.3390/jrfm16010031. https://elibrary.ru/oeybtw.

21. Chowdhury, S., Dey, P., Rodriguez-Espindola, O., Truong, L., Joel-Edgar, S., Bhattacharya, S., Abadie, A. (2023) Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human resource management review, 33(1), 100899. https://doi.org/10.1016/j.hrmr.2022.100899. https://elibrary.ru/zuamqa.

22. Grabowska, S., Saniuk, S. (2022). Assessment of the competitiveness and effectiveness of an open business model in the industry 4.0 environment. Journal of Open Innovation: Technology, Market, and Complexity, 8(1), 57. https://doi.org/10.3390/joitmc8010057. https://elibrary.ru/dqdenm.

23. Cernisevs, O., Popova, Ye., Cernisevs, D. (2023) Business KPIs Based on Compliance Risk Estimation. Journal of Tourism and Services, 14(27), 222-248. https://doi.org/10.29036/jots.v14i27.636. https://elibrary.ru/wpbcni.

24. Priyashantha, G., Chandradasa, A.H.I. (2023) Electronic human resource management (e-HRM) adoption; a systematic literature review. Sri Lanka Journal of Social Sciences, 46(1). https://doi.org/10.4038/sljss.v46i1.8573. https://elibrary.ru/efynpi.

25. Prasad, K., Nag, D., Kalavakolanu, S., Vaidya, R. (2023) The application of human resources information systems for enhancing output in agricultural companies. Journal of Social Economics Research, 10(4), 179-193. https://doi.org/10.18488/35.v10i4.3521. https://elibrary.ru/aoznkn.

26. Bhatia, A., Nangia, R. (2023) Impact of human resources information system on human resource strategies with empirical study of banking industry. Journal of Pharmaceutical Negative Results, 1034-1037. https://doi.org/10.47750/pnr.2023.14.S01.140. https://elibrary.ru/fscrkz.

28. Iakovets, A., Balog, M., Židek, K. (2022). The use of mobile applications for sustainable development of SMEs in the context of Industry 4.0. Applied Sciences, 13(1), 429. https://doi.org/10.3390/app13010429. https://elibrary.ru/exipyk.

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