The role of generative AI in improving the sustainability and efficiency of HR recruitment process
Abstract Generative artificial intelligence (GAI) is becoming increasingly important in business processes, including human resource management. GAI can offer the potential to automate repetitive tasks in recruitment processes, optimise decision making, and reduce administrative burdens. Although AI...
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| Format: | Article |
| Language: | English |
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Springer
2025-07-01
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| Series: | Discover Sustainability |
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| Online Access: | https://doi.org/10.1007/s43621-025-01484-3 |
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| author | Réka Koteczki Dániel Csikor Boglárka Eisinger Balassa |
| author_facet | Réka Koteczki Dániel Csikor Boglárka Eisinger Balassa |
| author_sort | Réka Koteczki |
| collection | DOAJ |
| description | Abstract Generative artificial intelligence (GAI) is becoming increasingly important in business processes, including human resource management. GAI can offer the potential to automate repetitive tasks in recruitment processes, optimise decision making, and reduce administrative burdens. Although AI can help increase operational efficiency, environmental pressures must also be taken into account. AI models require significant computing power, resulting in high energy consumption and increased CO2 emissions. This dichotomy may raise the question of whether the efficiency gains provided by GAI outweigh the environmental burden. This article examines the environmental impacts of GAI on HRM through a case study. The research combines qualitative and quantitative methods: expert interviews are used to explore practical applications, while calculations on energy consumption, costs, and emissions are carried out by comparing traditional and AI-based recruitment methods. The results of the case study showed that the integration of GAI led to efficiency gains. The time required for the recruitment process was reduced by 13.25 h, which could save thousands of man-hours per year. At the same time, costs and energy consumption and associated carbon emissions were reduced. The study highlights the duality of “AI for sustainability” and “sustainability of AI”, highlighting that while GAI can contribute to more sustainable corporate operations, its own environmental footprint raises questions about long-term sustainability. The results will provide HR professionals, decision makers, and organisations with practical insights into the potential for sustainable use of AI. |
| format | Article |
| id | doaj-art-58e6a06f189c4e9cb37af17106747c03 |
| institution | DOAJ |
| issn | 2662-9984 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Sustainability |
| spelling | doaj-art-58e6a06f189c4e9cb37af17106747c032025-08-20T03:03:19ZengSpringerDiscover Sustainability2662-99842025-07-016112810.1007/s43621-025-01484-3The role of generative AI in improving the sustainability and efficiency of HR recruitment processRéka Koteczki0Dániel Csikor1Boglárka Eisinger Balassa2 Vehicle Industry Research Center, Széchenyi István University Vehicle Industry Research Center, Széchenyi István University Vehicle Industry Research Center, Széchenyi István UniversityAbstract Generative artificial intelligence (GAI) is becoming increasingly important in business processes, including human resource management. GAI can offer the potential to automate repetitive tasks in recruitment processes, optimise decision making, and reduce administrative burdens. Although AI can help increase operational efficiency, environmental pressures must also be taken into account. AI models require significant computing power, resulting in high energy consumption and increased CO2 emissions. This dichotomy may raise the question of whether the efficiency gains provided by GAI outweigh the environmental burden. This article examines the environmental impacts of GAI on HRM through a case study. The research combines qualitative and quantitative methods: expert interviews are used to explore practical applications, while calculations on energy consumption, costs, and emissions are carried out by comparing traditional and AI-based recruitment methods. The results of the case study showed that the integration of GAI led to efficiency gains. The time required for the recruitment process was reduced by 13.25 h, which could save thousands of man-hours per year. At the same time, costs and energy consumption and associated carbon emissions were reduced. The study highlights the duality of “AI for sustainability” and “sustainability of AI”, highlighting that while GAI can contribute to more sustainable corporate operations, its own environmental footprint raises questions about long-term sustainability. The results will provide HR professionals, decision makers, and organisations with practical insights into the potential for sustainable use of AI.https://doi.org/10.1007/s43621-025-01484-3Generative artificial intelligence (GAI)Human resource management (HRM)Efficiency optimisationChatGPTSustainable development goals (SDGs)Interview |
| spellingShingle | Réka Koteczki Dániel Csikor Boglárka Eisinger Balassa The role of generative AI in improving the sustainability and efficiency of HR recruitment process Discover Sustainability Generative artificial intelligence (GAI) Human resource management (HRM) Efficiency optimisation ChatGPT Sustainable development goals (SDGs) Interview |
| title | The role of generative AI in improving the sustainability and efficiency of HR recruitment process |
| title_full | The role of generative AI in improving the sustainability and efficiency of HR recruitment process |
| title_fullStr | The role of generative AI in improving the sustainability and efficiency of HR recruitment process |
| title_full_unstemmed | The role of generative AI in improving the sustainability and efficiency of HR recruitment process |
| title_short | The role of generative AI in improving the sustainability and efficiency of HR recruitment process |
| title_sort | role of generative ai in improving the sustainability and efficiency of hr recruitment process |
| topic | Generative artificial intelligence (GAI) Human resource management (HRM) Efficiency optimisation ChatGPT Sustainable development goals (SDGs) Interview |
| url | https://doi.org/10.1007/s43621-025-01484-3 |
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