This study examines the adoption of Artificial Intelligence (AI) within Human Resource Management Information Systems (HRMIS) by employing a Systematic Literature Review (SLR) methodology. The analysis encompasses 28 Scopus-indexed articles published between 2021 and 2026 that investigate AI applications in areas such as Human Resource Information Systems (HRIS), algorithm-driven recruitment, performance management, employee experience enhancement, and the automation of HR-related processes. The findings reveal that AI has become an important enabler of organizational efficiency by streamlining HR operations, supporting evidence-based decision-making, accelerating talent acquisition activities, and improving the accuracy and consistency of performance evaluations. Furthermore, AI facilitates personalized employee services and contributes to a more responsive work environment. Despite these advantages, several concerns remain, including algorithmic bias, data privacy and security risks, limited transparency in automated decision-making, and challenges related to accountability and employee trust. Consequently, organizations should establish ethical governance mechanisms, strengthen technological and organizational readiness, and adopt human-centered system designs to maximize the long-term value and sustainability of AI-driven HR practices.
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