Aug 2026· Journal of Business and Digital Innovation· Vol 1, pp. 50-62· 0 citations· 23 references
TL;DR
The findings reveal that AI adoption in HRM is positively associated with both organizational performance and organizational efficiency, and HR process efficiency was found to play a mediating role in these relationships, indicating that improvements in HR processes are a key pathway through which AI generates organizational benefits.
Abstract
In the era of the Fourth Industrial Revolution, the use of artificial intelligence (AI) in human resource management (HRM) is increasingly recognized as a powerful tool for improving organizational performance and efficiency. However, despite growing interest in this area, there is still limited and fragmented evidence explaining exactly how AI adoption leads to these improvements. Guided by the Technology Acceptance Model (TAM), the Resource-Based View (RBV), and Dynamic Capabilities Theory (DCT), this study investigates how AI adoption in HRM contributes to organizational performance and efficiency through improvements in HR process efficiency. A cross-sectional survey was conducted among 452 HR personnel and employees working in information technology (IT)-related organizations in Lagos State, South-West Nigeria. Three hypotheses were tested using path analysis. The findings reveal that AI adoption in HRM is positively associated with both organizational performance and organizational efficiency. In addition, HR process efficiency was found to play a mediating role in these relationships, indicating that improvements in HR processes are a key pathway through which AI generates organizational benefits. Overall, this study contributes to the HRM and information systems literature by providing deeper insight into AI-enhanced HRM and offering evidence to support the integration of AI into organizations’ day-to-day operations.
In modern industrial arena Artificial Intelligence (AI) has become the integral tool to escalate the organizational performance such as improving operational efficiency, effective decision making and achieving sustainable competitive advantage. In the area of Human Resource Management (HRM), AI has been an indispensable part specially in the sector of staffing and recruitment, employee training and motivation, employee performance measurement, ensuring proper industrial relations and managing diversified workforce. However, in spite of enormous use of AI tool is HRM sector, there is not enough evidence that it creates significant impact on the enhancement of employee performance in an organization. This study examines the relationship between adopting AI in the sector of HRM to measure the organizational performance. Based on the Resource-Based-View (RBV) and Technology-Organization-Environment (TOE), the study states a theoretical model aligning AI adoption, AI aided HRM practices, organizational and employee performance. In this research design quantitative approach have been used where structured questionnaire were the main tool to gather data from various HR experts from various industries. In this study 380 respondents have been taken as sample and data were analyzed via spss and smart PLS to evaluate the reliability, validity and the effects of mediation. It is probable that uses of AI will have a positive impact in the employee and industrial performance. However, AI aided HRM has shown an enormous implication in the overall activities of an industry not fully but partially. The findings of the study expected to widen the opportunity further in the near future so that AI aided HRM activities can further perform better to achieve an organizations objective as smoothly as possible. This study has also shown the practical procedures for future leaders or managers to find a gateway from all the odds that may arise from this type of situation.
S. Siddiquee· International journal of res...· 0 citations
This study investigates how AI adoption enhances organizational innovation capability and, in turn, improves economic, environmental, and social dimensions of business performance, and links digital transformation with sustainability outcomes.
S. P, Sriharan M, S. P et al.· International Journal for Re...· 0 citations
Objective: This study aims to analyze the influence of Integration AI in e-HRM on Organization Performance through the mediating role of Effectiveness of HR Decisions and examine the role of Organizational Culture moderation in strengthening the relationship between Integration AI in e-HRM and Effectiveness of HR Decisions. This research was developed to explain the mechanism of organizational value creation using Artificial Intelligence (AI) in the practice of electronic Human Resource Management (e-HRM).
Design/Methodology/Approach: This study uses a quantitative approach with a cross-sectional survey design. Data was collected from 200 managers and Human Resource professionals at multinational manufacturing companies in the Riau Islands, Indonesia, who have implemented AI in e-HRM practices. The research model was developed based on the integration of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the Technology–Organization–Environment (TOE) Framework. Hypothesis testing was carried out using Covariance-Based Structural Equation Modeling (CB-SEM) with the help of AMOS.
Results: The results of the study show that the Integration of AI in e-HRM has a positive and significant effect on the Effectiveness of HR Decisions and Organization Performance. The effectiveness of HR Decisions has been shown to have a positive effect on Organization Performance and partially mediates the relationship between Integration AI in e-HRM and Organization Performance. In addition, Organizational Culture has been proven to strengthen the influence of AI Integration in e-HRM on the Effectiveness of HR Decisions. These findings show that AI creates organizational value through direct operational channels and strategic channels that occur through improving the quality of HR decisions.
Theoretical Implications: This study expands the application of UTAUT2 and the TOE Framework in the context of AI-enabled Human Resource Management by explaining the Effectiveness of HR Decisions as the main mechanism linking AI integration with improved organizational performance as well as identifying Organizational Culture as an organizational condition that influences the effectiveness of AI utilization.
Practical Implications: The research findings provide implications for organizations in designing HR digital transformation strategies that not only focus on the adoption of AI technology, but also on improving the quality of HR decisions and strengthening organizational cultures that support innovation, collaboration, and data utilization in decision-making.
Originality: This research offers an empirical model that explains the mechanisms of AI value creation in e-HRM through a combination of direct relationships, mediation, and moderation in one integrated conceptual framework. The study also provides empirical evidence from multinational manufacturing companies in Indonesia, which is still relatively limited in the literature on AI and Human Resource Management.
Ridhayati Farid, Yolanda Masnita, H. Yusran et al.· International journal of res...· 0 citations
Artificial intelligence (AI) and human resource management (HRM) are two closely intertwined areas that have gained increasing attention in management research. While AI technologies aim to enhance decision-making, efficiency, and innovation within organizations, HRM reflects a company’s ability to manage, engage, and develop its workforce effectively. However, despite the growing body of literature, existing reviews remain fragmented and often lack a comprehensive synthesis of how AI impacts HR functions and employee-related outcomes. Importantly, AI is not merely a technological tool; when strategically integrated into HR practices, it can significantly improve employee engagement, organizational effectiveness, and ethical governance. The objective of this study is to examine the integration of AI in HRM and its impact on employee involvement and organizational outcomes, with a specific focus on identifying the research gap related to the lack of integrated thematic and analytical perspectives in prior reviews, and identifying the key dimensions that influence successful implementation. To achieve this, a systematic review of the literature published between 2016 and 2025 was conducted using the Scopus database to ensure access to the most relevant studies. Predefined inclusion and exclusion criteria were applied, resulting in an initial selection of 2,385 articles. After removing duplicates and conducting a detailed analysis of abstracts and full texts, a final sample of 23 studies was retained. Unlike prior studies that adopt a predominantly descriptive approach, this review combines descriptive and qualitative content analysis to provide a structured thematic synthesis of the literature. The analysis highlights three main areas: AI adoption strategies, HR functions most affected by AI, and ethical and regulatory challenges associated with its use. Key factors influencing successful AI integration include employee involvement, management commitment, and the implementation of ethical governance frameworks. Organizations that implement AI in a structured and transparent manner tend to achieve higher engagement, improved decision-making, and enhanced organizational effectiveness. The findings suggest that future research should focus on increasing employee participation in AI-driven HR initiatives, developing robust ethical guidelines, and establishing appropriate regulatory frameworks to maximize the positive impact of AI on human resource management.
Rachida Goumrhare, Kaoutar El Moutchou, Meryem Harmaz et al.· Multidisciplinary Reviews· 0 citations
AI capability is a new strategic capability in the organization that goes beyond operational efficiency and can support the quality strategic decision-making, sustainable performance of an organization, and high decision quality. Though AI capability is evolving, current research remains disparate in how to transform an AI capability to a organizational value with the role of governance, leadership, and organizations capability. To solve this, in this study, a integrated conceptual framework grounded in the theory of resource-based view(RBV), dynamic capabilities theory(DCT) and the AI Governance literature is developed and empirically tested. In the model, the sequential relation between AI capability, AI governance, strategic decision quality, organizational agility, and organizational performance was proposed and the moderating role of digital leadership was examined. An explanatory sequential mixed-methods research design was used. The empirical analysis includes two phases. In the first phase, a cross-sectional survey of 446 senior executives and strategic decision makers of public and private organizations was conducted to empirically test the proposed integrated model using Partial Least Squares Structural Equation Modeling (PLS-SEM). In the second phase, qualitative data from 30 semi-structured interviews with senior executives was collected to gain a deep understanding of AI governance, digital leadership and organizational agility practices. Multi-group analysis further revealed differences in the proposed relationships for public and private organizations. Findings revealed that AI capability not only significantly strengthens the AI governance, and consequently the strategic decision quality, but it also improve the organizational agility, resulting in improved performance. Furthermore, digital leadership has a positive effect on reinforcing the association between AI governance and the strategic decision quality. Overall, this study integrates the technology capability, the organizational capability and the leadership capability to establish an AI-enabled strategic decision-making and performance management framework, and provides strategic insights for organizations that aim to realize greater value from their AI investments.
Dareen Alshamsi, Dr. Mohamed Manea Almansoori, Dalal S. Almansoori et al.· Journal of Intelligent Decis...· 0 citations
The study concludes that AI adoption serves as a strategic organizational capability that significantly enhances strategic planning effectiveness and suggests that organizations leveraging AI technologies are more likely to develop effective strategies, improve decision quality, enhance forecasting accuracy, and strengthen organizational adaptability.
Mark Ian C. Abrias, Nerissa M. Revilla· World Journal of Advanced Re...· 0 citations
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