The work aims to study user needs of infant early education toys through artificial intelligence technology and quantitative analysis to provide reference ideas for the design and development of product. Firstly, python crawlers were used to capture WeChat official account text related to infant early education toys, artificial intelligence technology was used to automatically filter the captured text data, and initial user needs was analyzed through focus group discussions.Then, the fuzzy Kano questionnaire was used to classify the initial user needs, to obtain the must-be needs, one-dimensional needs, attractive needs, indifferent needs and reverse needs. Further, technique for order preference by similarity to an ideal solution was used to calculate and rank the importance of one-dimensional needs and attractive needs, and the needs indicators ranking first in importance were retained to determine the final summary of needs indicators for infant early education toys. Finally, actual infant early education toys were designed to verify the effectiveness of the method. With the help of artificial intelligence technology and quantitative analysis methods, the importance of user needs could be more accurately studied, and the user satisfaction could be effectively improved, which conforms to the market trend of the design and development of infant early education toys.