Jul 2026· Sa Journal of Human Resource Management· Vol 24· 0 citations· 18 references
TL;DR
How AI adoption is perceived by HRM practitioners to relate to experiences of the impostor phenomenon is explored and the implications of IP for practitioners’ perceived professional confidence in AI-driven contexts are examined.
Abstract
Orientation: The global adoption of artificial intelligence (AI) is transforming organisations, including in South Africa, where human resource management (HRM) professionals increasingly use AI-enabled systems. While AI offers efficiency, it creates psychological challenges, notably the impostor phenomenon (IP), where professionals doubt their competence and credit success to external factors like AI.
Research purpose: This study explored how AI adoption is perceived by HRM practitioners to relate to experiences of the IP and examined the implications of IP for practitioners’ perceived professional confidence in AI-driven contexts.
Motivation for the study: Despite growing research on AI-in-HRM, its psychological impact remains understudied. Addressing this gap is vital to ensure AI adoption enhances performance without undermining professional confidence.
Research approach/design and method: A qualitative design was employed. Semi-structured online interviews were conducted with HR managers in South Africa (n = 15). Data were transcribed verbatim and analysed using thematic analysis to generate key themes.
Main findings: Participant accounts suggest that AI adoption heightened feelings of self-doubt among HRM professionals, with many attributing workplace achievements to AI systems, luck or external support. Participants described IP as eroding their confidence, reducing ownership of achievements and affecting work engagement.
Practical/managerial implications: HR leaders should embed AI training within human resource development (HRD) programmes, implement performance appraisal systems that recognise both human and AI contributions, and design interventions to strengthen self-efficacy.
Contribution/value-add: This study offers interpretive insights into how IP is experienced in AI-driven contexts and offers actionable insights for fostering resilience and adaptability among HRM professionals in South Africa.
This empirical study examines the role of artificial intelligence (AI) technologies in modernizing human resource management (HRM) practices within IT companies in Uttar Pradesh, India, focusing on their impact on the working environment and associated implementation challenges. Drawing from a descriptive-analytical research design, primary data were collected via structured Likert-scale questionnaires from 279 IT professionals and HR managers in key hubs like Noida and Lucknow, supplemented by secondary sources from academic journals. Descriptive statistics and one-sample t-tests reveal moderate AI adoption (mean AI usage level: 3.11), with neutral-to-slightly positive perceptions on enhancements to HR efficiency (mean: 2.97), bias reduction (mean: 2.99), employee experience (mean: 3.12), and work environment (mean: 2.94). AI demonstrates statistically significant contributions to talent retention (t=2.191, p=0.029, mean: 3.18), enabling proactive strategies through predictive analytics to mitigate high attrition risks prevalent in the region's emerging IT sector. Challenges such as data privacy concerns (mean: 3.05), fear of job displacement (mean: 3.00), and lack of AI skills (mean: 2.96) are perceived as moderate and non-significant barriers (p>0.05), indicating manageable hurdles rather than impediments to adoption. Findings align with prior literature, underscoring AI's potential to automate recruitment (e.g., ATS, chatbots), performance evaluation, and onboarding while elevating HR's strategic role amid talent competition and skill gaps in Uttar Pradesh. This research highlights the need for phased AI integration, workforce upskilling, and robust data governance to unlock broader benefits, particularly in retention and efficiency. Future studies should explore longitudinal effects and comparative analyses across Indian regions to inform policy and practice.
Bhavana Bhardwaj, Anurag Shakya· Adolescência e Saúde· 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
Artificial Intelligence (AI) is progressively reshaping Human Resource Management (HRM) practices globally, signaling a significant revolution in the model of practice. However, the use of AI driven HRM processes is quite limited in Sri Lanka's apparel industry. In response to this gap, current study explores the reasons for non-adoption of AI in HRM within a leading apparel company in Sri Lanka.The study is led by the interpretivist paradigm using an inductive reasoning process. The semi-structured and indepth interviews were carriedout for data collection with HR professionals and other selected managers of the study apparel company. Findings indicated the number of interrelated factors influencing the non-adoption of AI, including lack of training and awareness, a lack of technological infrastructure, fear of job loss, a lack of commitment from management teams, and insufficient support from the government. Moreover, norms of practices in the industry, the emphasis placed on human involvement, and traditional practices in HRM were viewed as significant barriers. These findings contribute to a non-use of AI driven HRM is an issue of a technological nature, but are significantly impacted by cultural, structural, and behavioral influences on the organization.
B. Lahiru, K. G. G. S. Karunathilaka· Kelaniya Journal of Human Re...· 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 reshaping how organisations create, validate, share and use workforce knowledge. Despite rapid growth, research on AI in human resource management (HRM) remains fragmented across HRM, information systems and knowledge management. This study maps the intellectual structure of the Scopus-indexed literature and interprets its major research streams through a knowledge management lens. Drawing on 693 peer-reviewed journal articles published between 1991 and 2025, it combines performance analysis, bibliographic coupling, keyword co-occurrence mapping and thematic evolution with a focused qualitative reading of influential works in each cluster. The findings show rapid growth since 2019 and three dominant but weakly integrated streams: AI adoption and HR analytics; algorithmic decision-making, fairness and governance; and human-AI collaboration. The qualitative interpretation shows that these streams differ not only in topic but also in their assumptions about workforce knowledge: whether it is treated as data to be codified and optimised, as a source of bias and ethical risk, or as a human capability that intelligent systems can augment. The study contributes to knowledge management by showing that AI-HRM research is organised around competing processes of knowledge codification, validation, transfer and use, while giving less attention to knowledge creation, tacit expertise and employee-side knowledge agency. It concludes with a research agenda on knowledge governance, employee experience and cross-database validation. The Scopus-only corpus is acknowledged as a limitation.
Rasti Blbas, D. Lewicka· European Conference on Knowl...· 0 citations
The integration of artificial intelligence (AI) into organizations is reshaping management practice, competitive strategy, and the experience of work, yet scholarship remains fragmented across disciplines and is predominantly Western-centric. This systematic literature review synthesizes interdisciplinary evidence on how AI transforms leadership and management functions, drives business model innovation, and alters workplace dynamics, with particular attention to Southeast Asian and Philippine contexts. Peer-reviewed, English-language journal articles published between 2016 and 2025 addressing the organizational, strategic, or workforce implications of AI were included; purely technical studies and non-peer-reviewed materials were excluded from the corpus, with institutional reports used only for contextualization. Scopus, Web of Science, ABI/INFORM, Business Source Complete, and the ACM Digital Library were searched. Screening followed the PRISMA 2020 guidelines: 1,245 records were identified, and 128 studies met all inclusion criteria and were synthesized thematically. First, AI integration facilitates an augmented leadership model in which effective managers combine human judgment with algorithmic capability. Second, AI operates as a strategic capability that enables adaptive, data-centric business models. Third, workplace dynamics exhibit a bifurcation effect whereby AI augments some roles while displacing or deskilling others. The review contributes an integrative tripartite framework connecting leadership, strategy, and workforce transformation, and identifies priorities for research and policy in emerging economies. No protocol was registered.
Teodulfo Mahilum, Michelle Go, Rosemarie Magno et al.· JPAIR Multidisciplinary Rese...· 0 citations
