Collaborative Models for Ethical AI Integration in Human Resources
DOI:
https://doi.org/10.61978/shr.v1i1.525Keywords:
Artificial Intelligence, Human Resource Management, Organizational Structure, Digital Transformation, Collaborative Strategy, Algorithmic Fairness, Inclusive HR PolicyAbstract
This narrative review investigates the systemic and organizational factors influencing the adoption of artificial intelligence (AI) in human resource management (HRM). The study aims to synthesize current literature on how structural and social contexts affect the integration of AI technologies into HRM practices. Using a structured thematic analysis of recent scholarly contributions, the research explores the interplay between organizational culture, social systems, leadership dynamics, and collaborative strategies. The findings indicate that flat organizational structures and inclusive social systems significantly accelerate AI adoption, while hierarchical and siloed arrangements create barriers. Effective AI integration depends on transparent leadership, cross-functional collaboration, and adaptive HR policies that align technology with human-centered values. The review further underscores the role of algorithmic fairness, real-time performance analytics, and AI-powered recruitment systems in improving objectivity and operational efficiency. Collaborative strategies, involving IT experts, HR managers, ethicists, and external stakeholders, are critical to overcoming ethical and technical barriers. This review concludes that AI implementation in HRM requires a multi-level, systemic approach that goes beyond technological readiness. It calls for strategic alignment of organizational vision, inclusive policymaking, and intersectoral partnerships. The implications of this study suggest that AI, when ethically and strategically deployed, can reshape HRM practices to be more efficient, equitable, and sustainable.
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