The present study aimed to identify the components of AI-based instructional design involving collaboration between humans and artificial intelligence. The research comprised two phases: a human-assisted phase and an AI-assisted phase. In the human-assisted phase, a systematic review was conducted. Using the specified keywords, a total of 299 studies were identified.After reviewing the titles of the articles, 71 articles were deleted due to duplication, and 228 articles were identified for title and abstract review. In this review, 123 were excluded by applying the criteria, and after review, 20 studies were finally selected for in-depth analysis. In the artificial intelligence assistance section Copilot, Gemini, ChatGPT, and Cloud software were used with prompts titled "Components of AI-supported instructional design ", "Human and Artificial Intelligence Collaboration in Instruction design", "Instructional AI-supported instructional design and Its Components" and "Components of Instruction design with Artificial Intelligence Assistance" for 5 time periods. The content analysis method was used to analyze the data. The research results showed that AI-based instructional design includes 14 main components, which are: needs analysis, content, instructional partner, feedback, interaction, evaluation, adaptation, ethics, information and data, teaching method, personalization, goals and outcomes, automation, support. The research results also show that the human search section on AI-supported instructional design components in the literature focuses on assessment, teaching method, content, instructional partner, and learning goals and outcomes, and the AI response section emphasizes components such as interaction, evaluation, feedback, information and data, and support. Hence, it can be concluded that in order for AI to be used effectively in instructional design, attention should be paid to the aforementioned components.