Unravelling the impact of artificial intelligence on employee work: A triangulated approach using SPAR, ADO framework, and bibliometric analysis

Purpose This study investigates how artificial intelligence (AI) shapes employee work, emphasizing both the opportunities it creates and the challenges it introduces in modern organizations. Methodology A systematic literature review (SLR) using the SPAR-4-SLR protocol and bibliometric analysis, complemented by content analysis of highly cited studies. The Antecedents–Decisions–Outcomes (ADO) framework was applied to provide a structured understanding of AI adoption and its effects on employees. Findings AI can strengthen employee autonomy, skill development, collaboration, and organizational outcomes when supported by trust, leadership, and human-centered practices. At the same time, AI may also contribute to technostress, job insecurity, and role ambiguity. Originality/Contribution This study integrates the Technology Acceptance Model and the Job Demands–Resources theory into AI-related HR research while also introducing the concepts of AI maturity and employee resilience. By combining bibliometric, SLR, and ADO approaches, it provides a unique, holistic perspective on AI and workforce dynamics, addressing gaps in prior isolated studies.