AI is revolutionizing the summarization of financial reports by automating the extraction of key insights from lengthy and complex documents. Using Natural Language Processing (NLP) and machine learning, AI-powered tools can analyze earnings reports, annual filings, and central bank statements to provide concise, data-driven summaries. Abstractive and extractive summarization techniques help distill critical financial metrics, trends, and company performance indicators. Named Entity Recognition (NER) identifies key figures, such as revenue, net income, and growth rates, while sentiment analysis determines the overall tone of the report—whether optimistic, neutral, or negative. AI-driven summarization benefits traders, investors, and financial analysts by enabling quicker decision-making. It allows Forex traders to swiftly interpret macroeconomic reports, interest rate changes, and policy statements that impact currency movements. Additionally, AI enhances accessibility by translating and summarizing global financial reports for international investors. Despite challenges like contextual understanding and industry-specific jargon, AI-powered financial summarization significantly improves efficiency, helping market participants stay informed in a fast-paced financial environment.