Product innovation management plays a vital role in modern enterprises. It is one of the key factors in maintaining competitive advantage and is full of extremely important meanings. In a highly competitive market, companies must continue to innovate to stay ahead. Through the introduction of new products or enhancements to existing ones, companies can address the evolving needs of the market, retain current customers, and appeal to new ones. In recent years, deep learning, a machine learning method based on artificial neural networks, has demonstrated remarkable results in various fields. This article titled “Application and Effect Evaluation of Deep Learning in Product Innovation Management”, discusses the application of deep learning in product innovation management and evaluates its effect. First, the basic principles and techniques of deep learning are introduced, including the structure and training methods of neural networks. Then the particle swarm optimization algorithm is introduced. Then, the model is verified through case studies and empirical analysis, and the experimental results show that our model has good reliability. Finally, further research directions and suggestions are proposed to promote the application of deep learning in product innovation management.