This study aims to fill a gap in the literature by identifying and extracting critical success factors that impact the success of AI implementation. The factors are then categorized and presented in a process model that demonstrates the sequence of the factors and the interrelationships among them. The model is composed of three stages: pre-implementation, implementation, and post-implementation. The implementation is composed of three categories organization, process, and technology. Each of these categories contains several critical factors. The model presented helps both researchers and practitioners. Details, discussion, and future research opportunities are discussed in the paper.