Artificial Intelligence (AI) has transformed online learning by enabling intelligent feedback mechanisms that support personalized education. AI-based feedback systems provide real-time, adaptive, and data-driven responses to learners, enhancing engagement, motivation, and academic performance. This study examines the role of AI-powered feedback systems in online learning environments, exploring their architecture, applications, benefits, challenges, and future prospects. A mixed-method conceptual analysis was conducted using recent literature from educational technology, machine learning, and learning analytics domains. Findings indicate that AI-based feedback systems improve learner outcomes through personalized recommendations, automated assessment, predictive analytics, and continuous performance monitoring. However, concerns related to data privacy, algorithmic bias, and transparency remain significant barriers. The study concludes that AI-driven feedback systems have substantial potential to revolutionize digital education when implemented ethically and responsibly.