Intelligent college financial robots rely on process automation application analysis, yet flawed process analysis is a major issue. The process automation challenge in intelligent college finance robots cannot be solved by ordinary genetic algorithms, and the results are not sufficient. Consequently, this study examines the use of financial robot process automation in universities and suggests an AI-based application analysis of this technology in higher education. In order to minimize interference factors in process automation application analysis, the influencing elements are first found using computer science theory. The indicators are then split according to the needs of the study. Next, a method for analyzing process automation applications from an artificial intelligence viewpoint is developed using computer science theory. The outcomes of this study are then thoroughly examined. Using certain evaluation criteria, the MATLAB simulation results demonstrate that, when it comes to process automation application analysis impacting factor time and accuracy, the artificial intelligence viewpoint outperforms the classical genetic method.