The intersection of artificial intelligence (AI) and behavioral finance is transforming the way consumer financial behavior is understood, predicted, and influenced. This paper explores how AI technologies, including machine learning, natural language processing, and predictive analytics, are being integrated into behavioral finance to decode cognitive biases, emotional responses, and decision-making patterns. By analyzing large-scale consumer data, AI systems can identify anomalies in financial behavior, detect patterns of irrationality, and offer personalized financial advice, thus enhancing financial inclusion and literacy. The study highlights key applications such as robo-advisory services, sentiment analysis in market prediction, and AI-driven credit scoring. Additionally, the paper examines the ethical challenges related to algorithmic transparency, data privacy, and potential manipulation of consumer decisions. Through a synthesis of academic literature, industry reports, and case studies, the study offers a comprehensive understanding of how AI is reshaping behavioral finance, while emphasizing the need for regulatory oversight and ethical design in AI systems. This research underscores the potential of AI to foster more informed, equitable, and psychologically aware financial ecosystems, paving the way for innovation in financial decision-making and consumer engagement