This chapter explores the transformative role of artificial intelligence (AI) in personalized financial decision-making, highlighting how robo-advisors utilize advanced machine learning to detect and respond dynamically to investor behavioral biases such as loss aversion, overconfidence, anchoring, and recency effects. By employing predictive analytics and reinforcement learning models, robo-advisory platforms can anticipate investor behavior and proactively tailor interventions, significantly improving both financial outcomes and user satisfaction. Real-world case studies from wealth management and retirement planning illustrate the successful deployment of hyper-personalized strategies, demonstrating AI’s capacity for nuanced portfolio adjustments and behavioral nudges. Despite promising advancements, the chapter addresses critical ethical challenges, including transparency, informed consent, data privacy, and the risks of reinforcing demographic biases or manipulative practices. The chapter concludes by advocating continuous refinement of AI strategies to balance technological sophistication with ethical responsibility, ensuring personalized finance genuinely serves investor welfare and market integrity.