2026· Journal of Strategic Human Resource Management· 0 citations
TL;DR
Results show that AI complements HRM, but ethics must be taken into consideration for responsible and sustainable labour management, but ethics must be taken into consideration for responsible and sustainable labour management.
Abstract
The emergence of artificial intelligence (AI) in human resource management (HRM) has transformed traditional human resource (HR) processes such as recruiting, performance appraisal, employee surveillance, and decision-making. While AI increases efficiency, accuracy, and data-driven decision-making, it also raises ethical challenges for organisations. Ethical Issues of AI in HRM – Algorithmic Bias, Transparency, Data Privacy, Responsibility. Research shows that AI-driven systems can inadvertently reinforce biases in hiring and promotion based on flawed data inputs or constrained design. AI algorithms for HR applications are often inscrutable, leaving HR professionals in a ‘black box’ scenario, where it is difficult to comprehend or justify certain decisions. Like most contemporary topics, ethical issues related to employee data privacy and surveillance can harm employee trust and company culture. Conceptually and analytically, this paper reviews AI ethics and HRM literature together with previously developed frameworks. It highlights the need for ethical standards and responsible deployment of AI to ensure fairness, accountability, and inclusiveness. Results show that AI complements HRM, but ethics must be taken into consideration for responsible and sustainable labour management.
Artificial Intelligence (AI) has significantly transformed Human Resource Management (HRM), causing ethical and governance challenges around algorithmic decision making. Despite growing research, the literature is conceptually fragmented and lacking an integrative framework to connect applications of AI models with ethical and governance strategies. This study aims to conduct a systematic literature review and develop a comprehensive governance framework for responsible AI use in HRM. A systematic literature review of 84-peer reviewed articles from 2018 to 2024 was conducted through applying PRISMA protocol. Identifying five core HR-functions and nine major ethical issues. Findings indicate that AI adoption is prominent in recruitment, selection, and performance management, where algorithms shape evaluative decisions. Thus, the applications are associated with bias, transparency, and accountability issues. We develop an integrative governance framework highlighting maturity model, legitimacy, and accountability theory to address these concerns. Shifting the focus from AI adoption to governance, advancing literature on AI-HRM, and creating a clear framework for ethically responsible AI management. Offering actionable practical insights for HR professionals, AI developers, and policy makers on the implementation of responsible AI.
Artificial Intelligence (AI) has emerged as a transformative force in Human Resource Management (HRM), reshaping
traditional HR practices through intelligent automation, predictive analytics, and data-driven decision-making. AI-powered
technologies such as machine learning, natural language processing (NLP), robotic process automation (RPA), and generative
AI are increasingly used to streamline recruitment, employee onboarding, performance management, workforce planning,
learning and development, and employee engagement. These innovations enable organizations to improve operational efficiency,
reduce administrative costs, enhance employee experiences, and support strategic decision-making.
Despite its significant advantages, AI adoption in HRM also raises critical challenges related to algorithmic bias, data privacy,
ethical concerns, transparency, legal compliance, and workforce displacement. Organizations must therefore adopt responsible
AI governance frameworks that balance technological innovation with fairness, accountability, and human oversight.
This article reviews the applications of AI in HRM, examines its opportunities and challenges, and explores future prospects for
AI-enabled workforce management. The study concludes that AI should complement rather than replace human judgment,
enabling HR professionals to focus on strategic and value-added activities while ensuring ethical and inclusive workplace
practices.
Dilawar Hussain· International Journal for Re...· 0 citations
A new era for human resources is beginning, driven by the use of artificial intelligence (AI) and people analytics to inform human resources (HR) decisions. This report presents an integrated, multi-disciplinary review of the current state-of-the-art of using AI and people analytics in HR, based upon established theoretical models from information systems, organizational behavior, ethics, etc. The report describes how traditional descriptive HR metrics have evolved to predictive and prescriptive HR analytics through the application of machine learning, natural language processing and algorithmic decision systems. In addition to providing examples of AI/people analytics applications throughout recruitment, performance management, retention, workforce planning and employee wellbeing, the report also assesses both the positive impacts of AI/people analytics to enable HR decisions to be made more quickly, efficiently and strategically; as well as the significant negative implications of adopting these technologies - i.e. Algorithmic bias, erosion of employee privacy, distrust of employees toward HR systems, deskilling of HR professionals. Additionally, this report reviews ethical and legal frameworks related to fairness, accountability, transparency and the General Data Protection Regulation. Based on a synthesis of recent empirical and conceptual scholarship (2015 – 2025), the report argues that although AI and people analytics represent unparalleled opportunities for enhancing the quality and effectiveness of HR decisions; un-critically adopting them will lead to institutionalized biases, diminished employee dignity and degradation of the relational core of human resource management. Therefore, the report advocates for a human-centered augmented intelligence approach to HR where ethical principles are embedded within system design and human discretion is preserved. Finally, the report outlines a forward-looking research agenda centered around explainable AI, algorithmic literacy among HR professionals and co-design of analytics systems by employees.
Nancy Ayongo Odoi Opong, K. Yeboah, Joseph Manasseh Opong et al.· IRASS Journal of Multidiscip...· 0 citations
Artificial Intelligence (AI) is steadily reshaping the way organisations recruit, train, evaluate, and retain their workforce. From resume screening chatbots to predictive analytics for attrition, AI-enabled tools promise faster decisions, lower administrative costs, and more objective people practices. Yet the adoption of AI within Human Resource Management (HRM) in India and elsewhere remains uneven, and many organisations struggle to move beyond pilot projects. This paper examines the principal barriers that restrict the effective integration of AI into HRM functions, drawing on secondary literature and conceptual analysis. Eight interlinked barrier categories are identified and discussed: technological and infrastructural constraints, financial limitations, organisational and structural rigidity, skill and competency gaps, employee resistance and psychological apprehension, ethical and algorithmic-bias concerns, data privacy and security risks, and cultural or change-management challenges. The paper argues that these barriers rarely act in isolation; rather, they reinforce one another, so that a purely technical fix (for example, better software) is unlikely to succeed unless matched by investment in skills, transparent governance, and change communication. The study concludes with practical recommendations for HR practitioners and policy makers, and outlines directions for future empirical research, including sector-wise and cross-cultural comparisons of AI adoption in HRM.
CT. Vasantha, S. Bharathi· International Journal of Cre...· 0 citations
Artificial intelligence (AI) is increasingly being applied in human resource management, from recruitment, assisting with HR issues and scheduling to training, performance evaluation, and workforce planning. This article compiles 19 documents that have been checked for publication information and relevance to the research content. The results show that AI can help HR departments process tasks faster, implement more consistent processes, and support the personalization of certain activities. However, the effectiveness of implementation depends on the intended use, data quality, suitability of the assessment methodology, user capabilities, and accountability mechanisms. Key risks include algorithmic bias, uninterpretable results, negative reactions from candidates and employees, personal data breaches, vendor dependence, and a tendency to over-rely on system-generated results. Based on this, the paper proposes a framework for responsible AI deployment consisting of six components: defining purpose and risk levels; data governance; relevance and fairness assessment; ensuring human oversight and decision-making; transparency and review; and continuous monitoring and capacity building. This framework defines AI as a supporting tool, not a replacement for the responsibilities of managers
M.A. Nguyen Thu Huong· International Journal of Sci...· 0 citations
It is concluded that while AI offers significant opportunities for improving HR effectiveness, organizational performance, and employment relations, successful implementation requires a balanced approach that integrates technological innovation with human-centered management practices and responsible workplace governance.
Habiganuchi Godfrey Bekwe, Nathaniel A. Ngerebara· International journal of res...· 0 citations