Research on the Application of Artificial Intelligence in Career Planning Decision Support System

This paper proposes a career planning decision support system based on artificial intelligence, aiming to improve the intelligence and accuracy of the decision-making process through a multi-task learning algorithm. The system comprehensively considers multiple factors such as individual ability, interest, personality characteristics and market demand, and predicts and recommends the most suitable career path by building a deep learning model. The system adopts a multi-task learning strategy to optimize the learning process of multiple related tasks at the same time, which can improve the generalization ability and accuracy of the model in multiple dimensions. This paper introduces a multi-task learning model based on neural networks, and evaluates its application effect in career planning through data set training and simulation analysis. The system can effectively provide personalized career development suggestions based on the user's personal information and the dynamic changes of the career market. Through comparative experiments, this paper verifies the superiority of the model in prediction accuracy and recommendation effect, and can maintain high robustness and adaptability in different scenarios. The model performs well on a variety of test data sets, with an accuracy of more than 90%. At the same time, compared with traditional algorithms, it has significantly improved career matching and user satisfaction.