The Intersection of Artificial Intelligence and Economic Forecasting Transforming Financial Models for Greater Predictive Accuracy

Abstract

This paper examines how four AI subfields machine learning, deep learning, and natural language processing are enhancing the field of economic forecasting by providing new forms of insight and more flexibility in economic trend analysis. AI in economic forecasting is disrupting economic models, and its impact provides more precision over traditional financial models. New challenges arise with complexity in the global economy where traditional theories and structures remain ineffective in the fast delivery of data to equip economists with the relevant information on the state of the economy. The features of the main algorithms used in machine learning and natural language processing are compared and evaluated in view of their possibilities for handling extensive data and predicting economic tendencies and values. This research indicates the implementation of AI and the uses for AI in economic modeling, as well as the issues that may arise, such as data protection and model explainability. The evidence suggests the use of AI in enhancing the precision and flexibility of various economic forecasting models. AI provided stakeholders with a useful and reliable strategy for forecasting economic changes, market trends, and the critical issues within specific industries. It sees that incorporating AI in economic forecasting is possible and does offer transformative benefits, given that, though not only seasoned with ethical dilemmas and data management issues, it does provide a more solid and stronger form-based decision-making in a fast-changing economic environment.