This paper aims to determine the outcomes of Artificial Intelligence (AI) proliferation into Human Resource Management (HRM) in the context of employee performance. The extant literature was examined using the methodology of Systematic Literature Review. Data was primarily collected from Scopus. The study identified major determinants of employee performance and termed them as performance predictors. The impact of AI was evaluated under the bi-dimensional aspects of direct and indirect performance predictors. The study identified three direct performance predictors namely decision-making, performance feedback, and training effectiveness. The indirect performance predictors were engagement, trust in technology usage, job insecurity and turnover intention, and AI anxiety and stress. The review further revealed trust as the most crucial construct in employees’ acceptance of AI. The findings suggested that trust could be further strengthened to diminish the effects of negative performance predictors. The implications for theory and practice have been discussed along with the directions of future research.