THE ROLE OF AI-POWERED FINANCIAL AGENTS IN ENHANCING DECISION-MAKING AND RISK MANAGEMENT IN MODERN BUSINESS ENVIRONMENTS

Abstract

The integration of Artificial Intelligence (AI) in financial decision-making and risk management has transformed modern business environments, offering more precise, data-driven insights for optimizing financial strategies. AI-powered financial agents, utilizing machine learning algorithms and advanced data analytics, enable businesses to analyze vast datasets, predict market trends, and enhance strategic decision-making. This research investigates the quantitative impact of AI-powered financial agents on decision-making processes and risk management within business environments. The study combines statistical analysis of real-world financial data with experimental simulations of AI-agent interventions. The research utilizes a purposive sampling approach, focusing on a range of industries including banking, investment, and corporate finance, to examine how AI agents influence financial outcomes, improve risk assessment accuracy, and facilitate optimal resource allocation. The study employs regression models, machine learning classifiers, and risk simulation techniques to quantify AI's effectiveness in financial decision-making. Findings indicate a significant improvement in the accuracy of financial predictions, a reduction in operational risks, and enhanced profitability through AI-driven strategies. The research highlights the role of AI in modernizing financial management by fostering more informed, adaptive, and resilient business practices in complex market conditions.