The purpose of this study is to develop a process theory explaining the “adoption and advancement of artificial intelligence in human resource (HR) processes” and to clarify the dynamic relationships among conditions, mechanisms, and outcomes over time. The research was conducted using the logic of classic grounded theory (Glaserian approach), and data were collected through 23 semi-structured interviews with HR managers from Iran’s top companies. Data were analyzed through open, selective, and theoretical coding. Findings indicate that this trajectory begins with environmental triggers (competitive pressure and changes in market needs) and becomes actionable through the simultaneous formation of two types of readiness: organizational readiness (infrastructure, data governance, security/privacy, and cross-unit coordination) and HR unit readiness (deployment strategy, knowledge and awareness, needs assessment, cross-functional alignment, change management, and culture building). The transition from limited implementation to sustained integration depends on two key mechanisms—top management support and trust in technology—while ecosystem strengthening, through broader enabling conditions and vendor support, facilitates the process by reducing learning costs, supporting localization, and enhancing assurance regarding data security. In terms of outcomes, AI can increase productivity, accuracy, and coordination, yet it may also generate job-related fears, resistance to data-driven management, and a weakening of human interaction. These dual outcomes operate as feedback, strengthening or undermining the advancement path and prompting ongoing recalibration over time