From automation to augmentation: Human resource's journey with artificial intelligence Article Swipe
María Bastida Domínguez
,
Alberto Vaquero García
,
Miguel Anxo Vázquez Taín
,
María Luisa del Río Araújo
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.jii.2025.100872
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.jii.2025.100872
This article examines the strategic integration of artificial intelligence (AI) in human resource management (HRM), highlighting both its opportunities and its challenges. While AI can improve HRM functions such as recruitment, performance evaluation and employee development, it also raises concerns related to algorithmic bias, technostress and resistance to change. To navigate these complexities, we present a structured two-tiered model that balances algorithmic efficiency with human-centred workforce development. Unlike previous studies that explore AI-driven human resource management in isolation, this research provides a comprehensive strategy for AI adoption that improves employee engagement, optimises HR decision-making and fosters organisational resilience. In addition to outlining the role of AI in human resource management, we explore its practical implications, ethical considerations and associated risks, offering strategies to mitigate bias, promote transparency and foster organisational readiness for AI-driven transformation. We also emphasise the importance of pilot studies and empirical validation to assess the model's effectiveness in diverse organisational contexts. By providing a structured roadmap for AI integration, this study contributes to the ongoing discourse on how human resource management can lead, rather than simply adapt to, AI-driven workforce transformation.
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- OA Status
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All OpenAlex metadata
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https://openalex.org/W4410384575Canonical identifier for this work in OpenAlex
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https://doi.org/10.1016/j.jii.2025.100872Digital Object Identifier
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From automation to augmentation: Human resource's journey with artificial intelligenceWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-05-15Full publication date if available
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María Bastida Domínguez, Alberto Vaquero García, Miguel Anxo Vázquez Taín, María Luisa del Río AraújoList of authors in order
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https://doi.org/10.1016/j.jii.2025.100872Publisher landing page
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.jii.2025.100872Direct OA link when available
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Automation, Engineering, Resource (disambiguation), Artificial intelligence, Computer science, Operations management, Engineering management, Business, Mechanical engineering, Computer networkTop concepts (fields/topics) attached by OpenAlex
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7Total citation count in OpenAlex
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2025: 7Per-year citation counts (last 5 years)
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| abstract_inverted_index.employee | 34, 89 |
| abstract_inverted_index.examines | 2 |
| abstract_inverted_index.improves | 88 |
| abstract_inverted_index.mitigate | 123 |
| abstract_inverted_index.navigate | 50 |
| abstract_inverted_index.offering | 120 |
| abstract_inverted_index.previous | 68 |
| abstract_inverted_index.provides | 80 |
| abstract_inverted_index.research | 79 |
| abstract_inverted_index.resource | 12, 74, 108, 172 |
| abstract_inverted_index.strategy | 83 |
| abstract_inverted_index.AI-driven | 72, 132, 181 |
| abstract_inverted_index.contexts. | 153 |
| abstract_inverted_index.discourse | 168 |
| abstract_inverted_index.emphasise | 136 |
| abstract_inverted_index.empirical | 143 |
| abstract_inverted_index.functions | 27 |
| abstract_inverted_index.optimises | 91 |
| abstract_inverted_index.outlining | 101 |
| abstract_inverted_index.practical | 113 |
| abstract_inverted_index.providing | 155 |
| abstract_inverted_index.readiness | 130 |
| abstract_inverted_index.strategic | 4 |
| abstract_inverted_index.workforce | 65, 182 |
| abstract_inverted_index.artificial | 7 |
| abstract_inverted_index.associated | 118 |
| abstract_inverted_index.efficiency | 62 |
| abstract_inverted_index.evaluation | 32 |
| abstract_inverted_index.importance | 138 |
| abstract_inverted_index.isolation, | 77 |
| abstract_inverted_index.management | 13, 75, 173 |
| abstract_inverted_index.resistance | 46 |
| abstract_inverted_index.strategies | 121 |
| abstract_inverted_index.structured | 56, 157 |
| abstract_inverted_index.two-tiered | 57 |
| abstract_inverted_index.validation | 144 |
| abstract_inverted_index.algorithmic | 42, 61 |
| abstract_inverted_index.challenges. | 21 |
| abstract_inverted_index.contributes | 164 |
| abstract_inverted_index.engagement, | 90 |
| abstract_inverted_index.integration | 5 |
| abstract_inverted_index.management, | 109 |
| abstract_inverted_index.performance | 31 |
| abstract_inverted_index.resilience. | 97 |
| abstract_inverted_index.development, | 35 |
| abstract_inverted_index.development. | 66 |
| abstract_inverted_index.highlighting | 15 |
| abstract_inverted_index.integration, | 161 |
| abstract_inverted_index.intelligence | 8 |
| abstract_inverted_index.recruitment, | 30 |
| abstract_inverted_index.technostress | 44 |
| abstract_inverted_index.transparency | 126 |
| abstract_inverted_index.complexities, | 52 |
| abstract_inverted_index.comprehensive | 82 |
| abstract_inverted_index.effectiveness | 149 |
| abstract_inverted_index.human-centred | 64 |
| abstract_inverted_index.implications, | 114 |
| abstract_inverted_index.opportunities | 18 |
| abstract_inverted_index.considerations | 116 |
| abstract_inverted_index.organisational | 96, 129, 152 |
| abstract_inverted_index.decision-making | 93 |
| abstract_inverted_index.transformation. | 133, 183 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.99799119 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |