Artificial Intelligence and Monetary Policy: Enhancing Central Bank Decision-Making through AI-Driven Text Analysis

Artificial Intelligence (AI) is revolutionizing the field of economics and finance, offering data-driven techniques for improving the analysis of macroeconomic policies. Among these, the integration of AI-based natural language processing (NLP) tools with monetary policy analysis is an emerging frontier. Central banks around the world, particularly the European Central Bank (ECB), rely heavily on public communication to shape market expectations and manage economic stability. However, the interpretation of these communications has traditionally been subjective and inconsistent. This research explores how AI, through machine learning-powered text analysis, can significantly improve the forecasting and interpretation of central bank policy decisions. Using real-world ECB statements as a dataset, the study applies NLP models to classify policy sentiment into expansionary, restrictive, or neutral categories. Findings indicate that AI-based analysis can uncover subtle linguistic cues in policy texts, enhance predictive models when combined with macroeconomic indicators, and ultimately improve decision-making for policymakers, investors, and economists. This paper highlights the transformative role AI is playing in modern monetary policy frameworks and offers a roadmap for its future integration into central banking systems.