The purpose of this study is to develop an educational content system for early childhood artificial intelligence education. For the purpose of the study, FGI was conducted on five early childhood education and artificial intelligence experts. The experts' claims were analyzed using the semantic interpretation method. The meaning interpretation method uses meaning compression - meaning categorization - meaning structuring. The experts' claims were condensed into 43 meanings. The 43 meanings were composed of 12 contents ranging from 'Human thinking process, computing ability, Principles and history of AI, Utilization of AI technology, Concept of data, Creative expression of AI, AI hardware configuration for creative convergence problem solving, Exploration and use of AI tools for creative and convergent problem solving, Creation of AI for creative and convergent problem solving, Interest in AI, Living with AI, Ethical use and attitudes of AI' using categorization. The 12 contents were organized into four categories, ranging from semantic structuring to Computational Thinking, AI and data, Creative convergence Problem solving, AI ethics. The results of this study are valuable in that they can serve as a basis for constructing artificial intelligence education in the field of early childhood education.