Research prospects for improving production efficiency through artificial intelligence models in the context of the digital economy

Abstract

In this study, the influence of artificial intelligence technologies on production efficiency and forecasting
efficiency are studied in comparison with traditional econometric models. Data are analyzed using machine learning
algorithms and econometric methods. The research results show that methods based on artificial intelligence, espe
cially in dynamic and complex conditions, surpass econometric models in terms of accuracy and flexibility. However,
econometric models are important in understanding explanatory outcomes and cause-and-effect relationships. The
study emphasizes the need for a hybrid approach that uses the strengths of AI and econometric models to optimize
production efficiency in the digital economy.