DIP: 18.02.030/20251003 
DOI: 10.25215/2455/1003030 
Abstract
Artificial Intelligence (AI) has emerged as a transformative tool in the realm of predictive economic forecasting, offering increased accuracy, speed, and adaptability in analyzing complex economic data. Traditional econometric models often fall short in capturing the dynamic and non-linear relationships among economic variables. In contrast, AI-driven approaches—such as machine learning, neural networks, and natural language processing—enable the integration of large and diverse datasets, uncover hidden patterns, and adapt to evolving market conditions in real-time. This paper explores how AI enhances economic forecasting by improving decision-making in areas such as monetary policy, financial market analysis, risk assessment, and business planning. It also examines the challenges associated with data quality, model transparency, and ethical considerations. Overall, the study underscores AI’s potential to complement and, in some cases, surpass traditional forecasting methods while emphasizing the importance of human oversight and interdisciplinary collaboration for responsible and effective implementation.
The author(s) appreciates all those who participated in the study and helped to facilitate the research process. 
The author(s) declared no conflict of interest. 
ISSN 2455-670X