| تعداد نشریات | 49 |
| تعداد شمارهها | 1,269 |
| تعداد مقالات | 10,971 |
| تعداد مشاهده مقاله | 22,473,378 |
| تعداد دریافت فایل اصل مقاله | 15,146,434 |
نقش و جایگاه هوشمصنوعی و یادگیری ماشینی در بهسازی منابع انسانی: کاربردها و چالشها | ||
| مطالعات نوین در علوم تربیتی | ||
| مقاله 2، دوره 1، شماره 2، آذر 1404، صفحه 27-43 اصل مقاله (701.79 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.30473/ns.2026.77083.1036 | ||
| نویسندگان | ||
| اکبر جدیدی محمد آبادی1؛ فروزان آموسی* 2؛ مریم حسین زاده3 | ||
| 1دانشیار گروه علوم تربیتی، دانشگاه پیام نور، تهران، ایران | ||
| 2علوم تربیتی، ادبیات و علوم انسانی، دانشگاه پیام نور،تهران، ایران | ||
| 3دانشجوی دکتری اقتصاد، گروه اقتصاد، دانشکده مدیریت و اقتصاد، دانشگاه شهید باهنر کرمان، کرمان، ایران | ||
| چکیده | ||
| تغییر دنیای کسبوکار تحتتأثیر دادهها، فناوریهای دیجیتال و نیازهای پیچیده سازمانها، باعث ناکارآمدی روشهای سنتی مدیریت منابع انسانی شدهاست. هوشمصنوعی (AI) و یادگیری ماشینی (ML) بهعنوان دو ابزار تحولآفرین در مدیریت منابع انسانی شناخته میشوند. چگونگی بهرهبرداری مؤثر رهبران سازمانها از این تحولات مهم میباشد. این فناوریها فرآیندهایی مانند جذب و استخدام، آموزش و توسعه، ارزیابی عملکرد، مدیریت استعداد، و برنامهریزی جانشینپروری را دگرگون کردهاند. هدف پژوهش حاضر، تبیین نقش و جایگاه هوشمصنوعی و یادگیری ماشینی در مدیریت منابع انسانی بر اساس شواهد پژوهشی موجود است. این مطالعه با روش مرور نظاممند و بر اساس چارچوبهای معتبر مرور پژوهش انجام شده و مقالات مرتبط پس از غربالگری و تحلیل، بهصورت نظاممند بررسی و طبقهبندی شدهاند. یافتههای پژوهش نشانمیدهد که بهکارگیری AI و ML میتواند به بهبود کیفیت تصمیمگیری، افزایش بهرهوری، کاهش سوگیریهای انسانی و ارتقای رضایت و تعهد کارکنان منجر شود. همچنین تحلیل دادههای گسترده و چندبعدی از طریق الگوریتمهای هوشمند، امکان شخصیسازی فرایندهای منابع انسانی، بهبود ارزیابی عملکرد، مدیریت استعداد و پیشبینی رفتارهای سازمانی را فراهم میسازد. در مجموع، استفاده اخلاقمحور و نظارتشده از هوشمصنوعی و یادگیری ماشینی میتواند زمینهساز مدیریت راهبردی و پیشدستانه منابع انسانی باشد و یافتههای این پژوهش میتواند بهعنوان مبنایی برای سیاستگذاری سازمانی و طراحی نظامهای نوین منابع انسانی مورد استفاده قرار گیرد. | ||
| کلیدواژهها | ||
| هوشمصنوعی؛ یادگیری ماشینی؛ بهسازی؛ منابع انسانی | ||
| عنوان مقاله [English] | ||
| The Role and Place of Artificial Intelligence and Machine Learning in Improving Human Resources: Applications and Challenges | ||
| نویسندگان [English] | ||
| Akbar Jadidi Mohammad abadi1؛ Fooroozan Amoosa2؛ Maryam Hosseinzadeh3 | ||
| 1Associate Professor, Department of Educational Sciences, Payam Noor University, Tehran, Iran | ||
| 2Educational Sciences, Literature and Humanities, Payam Noor University, Tehran, Iran | ||
| 3PhD student in Economics, Department of Economics, Faculty of Management and Economics, Shahid Bahonar University of Kerman, Kerman, Iran | ||
| چکیده [English] | ||
| The changing business world, influenced by data, digital technologies, and the complex needs of organizations, has made traditional human resource management methods ineffective. Artificial intelligence (AI) and machine learning (ML) are recognized as two transformative tools in human resource management. How organizational leaders effectively utilize these developments is important. These technologies have transformed processes such as recruitment and hiring, training and development, performance appraisal, talent management, and succession planning. The purpose of the present study is to explain the role and position of artificial intelligence and machine learning in human resource management based on existing research evidence. This study was conducted using a systematic review method and based on valid research review frameworks, and related articles were systematically reviewed and classified after screening and analysis. The research findings show that the use of AI and ML can lead to improved decision-making quality, increased productivity, reduced human biases, and enhanced employee satisfaction and commitment. Also, analyzing extensive and multidimensional data through intelligent algorithms allows for personalization of human resources processes, improvement of performance appraisal, talent management, and prediction of organizational behaviors. In summary, the ethical and supervised use of artificial intelligence and machine learning can pave the way for strategic and proactive human resources management, and the findings of this research can be used as a basis for organizational policy-making and the design of modern human resources systems. | ||
| کلیدواژهها [English] | ||
| Artificial Intelligence, Machine Learning, Improvement, Human Resources | ||
|
سایر فایل های مرتبط با مقاله
|
||
| مراجع | ||
|
Aggarwal, V & Stanley, D. S. (2025). Relationship among E-HRM, workforce agility, technostress and work engagement: Techno HRM engagement model (THEM). Psychological Studies, 70(1), 122-135. https://doi.org/10.1007/s12646-024-00811-4
Ammirato, S. Felicetti, A. M. Linzalone, R. Corvello, V & Kumar, S. (2023). Still our most important asset: A systematic review on human resource management in the midst of the fourth industrial revolution. Journal of Innovation & Knowledge, 8(3), 100403. https://doi.org/10.1016/j.jik.2023.100403.
Armstrong, M & Taylor, S. (2023). Armstrong's Handbook of Human Resource Management Practice: A Guide to the Theory and Practice of People Management. Kogan Page Publishers.
Basnet, S. (2024). Artificial Intelligence and machine learning in human resource management: Prospect and future trends. International Journal of Research Publication and Reviews, 5(1), 281-287.
Bolton, R. Dongrie, V. Saran, C. Ferrier, S. Mukherjee, R., S€oderstr€om, J., Brisson, S. and Adams, N. (2019), “The future of HR 2019: in the Know or in the No”, available at: https://assets.kpmg/ content/dam/kpmg/xx/pdf/2018/11/future-of-hr-survey.pdf (accessed January 2020).
Cabrera, R. M. Ganchozo, M. L. Rene, R. S. O. Bujaico, R. W. R. Samaniego, H. H & Bujaico, J. F. R. (2022). Impact Of Machine Learning In Human Resource Management: Towards The Modernization Of Leadership. Journal of Positive School Psychology, 6(2s), 290-299.
Brock, J. K. U & Von Wangenheim, F. (2019). Demystifying AI: What Digital Transformation Leaders Can Teach You about Realistic Artificial Intelligence. California Management Review, 61 (4) , 110- 134.. https://doi.org/10.1177/1536504219865226
Castellanos, S. (2019), “HR departments turn to AI-enabled recruiting in race for talent”, available at: https://www.wsj.com/articles/hr-departments-turn-to-ai-enabled-recruiting-in-race-for-talent 11552600459 (accessed January 2020).
Castillo, D. Canhoto, A. I & Said, E. (2021). The dark side of AI-powered service interactions: Exploring the process of co-destruction from the customer perspective. The Service Industries Journal, 41(13-14), 900-925. https://doi.org/10.1080/02642069.2020.1787993.
Chen, L. Hsieh, J. P. A & Rai, A. (2022). How does intelligent system knowledge empowerment yield payoffs? Uncovering the adaptation mechanisms and contingency role of work experience. Information Systems Research, 33(3), 1042-1071.
Cheng, M.M and Hackett, R.D. (2021), “A critical review of algorithms in HRM: definition, theory, and practice”, Human Resource Management Review, Vol. 31 No. 1, doi: 10.1016/j.hrmr.2019.100698. https://doi.org/10.1016/j.hrmr.2019.100698.
Choudhary, V. Marchetti, A. Shrestha, Y. R & Puranam, P. (2025). Human-AI ensembles: When can they work?. Journal of Management, 51(2), 536-569. https://doi.org/10.1177/01492063231194968.
Colther, C & Doussoulin, J. P. (2024). Artificial intelligence: Driving force in the evolution of human knowledge. Journal of Innovation & Knowledge, 9(4), 100625.
del Val Núñez, M. T. de Lucas Ancillo, A. Gavrila, S. G & Gandia, J. A. G. (2024). Technological transformation in HRM through knowledge and training: Innovative business decision making. Technological Forecasting and Social Change, 200, 123168.
Davenport, T. H & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
Deng, C. Li, H. Wang, Y & Zhu, R. (2024). The double-edged sword in the digitalization of human resource management: Person-environment fit perspective. Journal of Business Research, 180, 114738.
Di Vaio, A. Hassan, R & Alavoine, C. (2022). Data intelligence and analytics: A bibliometric analysis of human–Artificial intelligence in public sector decision-making effectiveness. Technological Forecasting and Social Change, 174, 121201.
Dima, J. (2024). The effects of artificial intelligence on human resource activities: A systematic literature review. Human Resource Management Review. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11188403/
Fenwick, A & Raghavan, S. (2024). Revisiting the role of HR in the age of AI: Bringing humans and machines closer. Frontiers in Artificial Intelligence, 7, 1272823. https://doi.org/10.3389/frai.2023.1272823
Madanchian, M. Hussein, N. Noordin, F & Taherdoost, H. (2024). From recruitment to retention: AI tools for human resource management. Applied Sciences, 14(24), 11750. https://doi.org/10.3390/app142411750
Mohammed, A. I. Mohammed, Z. F & Mohammad, H. A. (2022). The Effect of Compensation Management on Employee Performance: An Empirical Study in North Gas Company. World Bulletin of Management and Law, 7, 59-70.
Murugesan, U. (2023). A study of artificial intelligence impacts on human resource digitization in terms of measuring employee productivity, improving health and... Journal of Technology and Management. https://www.sciencedirect.com/science/article/pii/S2772662223000899
Nankervis, A. Connell, J. Cameron, R. Montague, A & Prikshat, V. (2021). 'Are we there yet? ' Australian HR professionals and the Fourth Industrial Revolution. Asia Pacific Journal of Human Resources, 59(1), 3-19.
Nawaz, N. (2020). Exploring artificial intelligence applications in human resource management. Journal of Management Information and Decision Sciences, 23(5), 552-563.
Ncube, T. R. Sishi, K. K & Skinner, J. P. (2025). The impact of artificial intelligence on human resource management practices: An investigation. SA Journal of Human Resource Management, 23, a2960. https://doi.org/10.4102/sajhrm.v23i0.2960
Pan, Y. Froese, F. Liu, N. Hu, Y & Ye, M. (2022). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. The International Journal of Human Resource Management, 33(6), 1125-1147.
Qamar, Y. Agrawal, R. K. Samad, T. A & Jabbour, C. J. C. (2021). When technology meets people: the interplay of artificial intelligence and human resource management. Journal of Enterprise Information Management, 34(5), 1339-1370.
Saadallah, M. Shahim, A & Khapova, S. (2024, June). Multi-method Approach to Human Expertise, Automation, and Artificial Intelligence for Vulnerability Management: Investigation of Challenges and Emerging Tensions. In IFIP International Conference on ICT Systems Security and Privacy Protection (pp. 410-422). Cham: Springer Nature Switzerland.
Sakka, F. El Maknouzi, M. E. H. Sadok, H. Ghadi, M. Y & Ismail, O. (2022). Human Resource Management in the era of Artificial Intelligence Future hr Work Practices Anticipated Skill set financial and legal Implications Human capital development in special economic zones the case of Dubai View project. Scientific Reports, 29(3), 67-75.
Sun, Y & Jung, H. (2024). Machine learning (ML) modeling, IoT, and optimizing organizational operations through integrated strategies: the role of technology and human resource management. Sustainability, 16(16), 6751.
Sun, Z. (2025). Determining human resource management key indicators and their impact on organizational performance using deep reinforcement learning. Scientific Reports, 15(1), 5690.
Suseno, Y. Chang, C., Hudik, M & Fang, E. S. (2022). Beliefs, anxiety and change readiness for artificial intelligence adoption among human resource managers: the moderating role of high-performance work systems. The InTernaTIonal Journal of human resource management, 33(6), 1209-1236.
Tewari, I & Pant, M. (2020, December). Artificial intelligence reshaping human resource management: A review. In 2020 IEEE international conference on advent trends in multidisciplinary research and innovation (ICATMRI) (pp. 1-4). IEEE.
Úbeda-García, M. Marco-Lajara, B. Zaragoza-Sáez, P. C., & Poveda-Pareja, E. (2025). Artificial intelligence, knowledge and human resource management: A systematic literature review of theoretical tensions and strategic implications. Journal of Innovation & Knowledge, 10(6), 100809
Vrontis, D. Christofi, M. Pereira, V. Tarba, S. Makrides, A., & Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. The International Journal of Human Resource Management, 33(6), 1237-1266. | ||
|
آمار تعداد مشاهده مقاله: 61 تعداد دریافت فایل اصل مقاله: 42 |
||