Empowering human resource management through artificial intelligence: A systematic literature review and bibliometric analysis

International journal of production management and engineering, Год журнала: 2025, Номер 13(1), С. 59 - 76

Опубликована: Янв. 31, 2025

Drawing on a systematic literature review and bibliometric analysis, this article examines the burgeoning field of Artificial Intelligence (AI) integration into Human Resource Management (HRM) practises. By evaluating 77 selected articles from two extensive databases, Scopus Web Science, study illuminates dynamic intersection AI technologies HRM, encapsulating profound implications for organisational individual aspects HR This analysis delineates three primary thematic areas: AI's transformative role in emerging paradigm human-AI collaboration, nuanced challenges opportunities presented by research contributes to academic discourse mapping current state applications identifying gaps proposing directions future research, emphasising need ethical frameworks strategic enhance Through scholarly endeavour, we aim offer comprehensive overview that aids practitioners researchers navigating complexities reshaping HRM towards more efficient, ethical, innovative

Язык: Английский

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Workforce training strategies and performance assessment in manufacturing environments: a preliminary investigation

Procedia Computer Science, Год журнала: 2025, Номер 253, С. 2399 - 2408

Опубликована: Янв. 1, 2025

Язык: Английский

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Crafting an organizational strategy for the new era: a qualitative study of artificial intelligence transformation in a homegrown Singaporean hotel chain

Business Process Management Journal, Год журнала: 2025, Номер 31(8), С. 104 - 123

Опубликована: Апрель 10, 2025

Purpose This study discusses the strategic integration of artificial intelligence (AI) within hospitality industry by examining experience a locally owned Singaporean hotel chain. It will address central gap in prior research’s lack attention to employees’ perspective AI adoption domestic chains. Design/methodology/approach Using grounded theory approach, this used thematic analysis in-depth interviews with ten managers chain who plan implement their Findings The results show that while offers many advantages, including lower costs, more effectiveness, and better customer experience, human intervention is still necessary provide individualized personalized service. emphasizes necessity well-rounded strategy uses AI’s potential without sacrificing crucial element characterizes best experience. Research limitations/implications Future research should study’s limitations using larger, diverse samples mixed methods explore adoption’s impact on hospitality. Practical implications Leaders foster an organizational culture emphasizing empowerment continuous learning integrate technologies successfully. insights from suggest can enhance employee experiences. However, effective strategies require considering cultural differences communicating benefits. Aligning implementation preferences, such as offering tech-driven solutions for younger, tech-savvy guests maintaining personal interaction less IT-savvy customers, key branding. strategic, differentiated approach ensures enhances operational efficiency maximizes guest satisfaction through tailored, services. Originality/value unique its focus Singapore, viewpoint has been largely overlooked previous research. By employing conducting managers, provides rich, qualitative into practical challenges benefits integrating sector. highlights advantages underscores indispensable role delivering high-quality service, thus balanced view industry.

Язык: Английский

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Data-Driven Decision-Making for Employee Training and Development in Jordanian Public Institutions

Data & Metadata, Год журнала: 2025, Номер 4, С. 886 - 886

Опубликована: Апрель 4, 2025

Introduction: AI-driven training and HR analytics have revolutionized employee development by offering personalized learning experiences optimizing skill enhancement. Public institutions are increasingly leveraging AI-based recommendations adaptive algorithms to improve workforce training. However, the effectiveness challenges of these approaches in real-world applications require further investigation.Methods: This study employed a descriptive analytical research design, utilizing both quantitative qualitative methods. Data was collected from 385 employees Jordanian public using structured surveys sentiment analysis feedback. Statistical techniques, including regression analysis, ANOVA, correlation were applied assess impact data analytics, recommendations, personalization on effectiveness.Results: The findings indicate that significantly effectiveness. Skill emerged as strongest predictor success (β = 0.7282, p < 0.001). Sentiment revealed 82% responded positively training, while 10% expressed concerns about content relevance interactivity. ANOVA results confirmed no significant differences across job roles, indicating equitable experiences.Conclusion: AI-powered is widely accepted but requires refinement address engagement concerns. Organizations should adopt hybrid approach, integrating with instructor-led guidance. Future explore long-term impacts performance organizational enhance digital strategies.

Язык: Английский

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Human-centred AI in industry 5.0: a systematic review

International Journal of Production Research, Год журнала: 2024, Номер unknown, С. 1 - 32

Опубликована: Окт. 2, 2024

Язык: Английский

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AI in the Workplace: Driving Employee Performance Through Enhanced Knowledge Sharing and Work Engagement

International Journal of Human-Computer Interaction, Год журнала: 2024, Номер unknown, С. 1 - 14

Опубликована: Дек. 9, 2024

In spite of the massive adoption AI technologies in organizational settings, there is a mix empirical evidence on how such affect employee performance. Underpinned theoretically by social exchange theory, this study investigates affects knowledge sharing and work engagement among employees. The present also moderating role perceived risk relationships between engagement. For analysis data collected from sample 447 Chinese workers, Structural Equation Modeling (SEM) was used. results found positive link both It that significantly influence Moreover, suggest correlation Additionally, research has drawn attention to fact moderates negatively relationship From these findings emanate important management implications for employees strategic use technology enhance

Язык: Английский

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Exploring the Effects of Industry 4.0/5.0 on Human Factors: A Preliminary Systematic Literature Review

IFAC-PapersOnLine, Год журнала: 2024, Номер 58(19), С. 539 - 544

Опубликована: Янв. 1, 2024

Язык: Английский

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