Abstract: This paper focuses on how to apply to the prediction of Korean economic trend by AI based econometrics. The traditionally, the economic trend analysis has been using the mathematic-based the prediction or the directions of changes in the economy using such as linear regression, ARIMA (Auto-Regressive-Integrated Moving Average) or VAR (Vector Auto-Regression) However, there are always many non-linearities in economic models and the issues during research process because of the process of linearization. On the other hand, the function of AI such as LLM (ChatGPT: Chat Generative Pretrained Transformer AI) technology neural network, and its combined learning system has a powerful learning (supervised learning, unsupervised learning, and reinforcement learning to train language). The generative AI model-based LLM (Large Language Model), TIM (Text-to-Image Model), and ITM (Image-to-Text Model) are rapidly increasing their functions and it has so many possibility for applying in everywhere because a new generation of user-friendly tool (Generative AI: Chat GPT) is useful for texts, images, and videos. It is very important to exactly understand and decide on how and what we have to do for the Korean economic analysis process for business, policy, and job patterns.
The first aim of his paper is to provide study strategies and simulation on how AI-based generative model and related technologies apply to economic analysis processing and what we have to prepare and study Korean econometrics.

Keywords: AI, LLM, Econometric analysis, Econometrics Model.

Downloads: | DOI: 10.17148/IARJSET.2026.13144