This study investigates the application of artificial intelligence (AI) to design hyper-personalized learning journeys within SAP SuccessFactors Learning Management System (LMS), aiming to align individual development with enterprise goals. By integrating SAP BTP services and machine learning models, the proposed framework dynamically recommends content based on employee behavior, skill gaps, and performance trends. Using a mixed-methods approach combining system review, expert interviews, and simulation on synthetic workforce datasets, the research demonstrates how AI improves content relevance, learning engagement, and internal mobility. The findings indicate that AI-driven personalization significantly enhances knowledge retention and accelerates time-to-skill development. Additionally, the study explores the role of embedded analytics, talent intelligence integration, and ethical AI governance in enterprise learning transformation. This paper concludes with scalable strategies for integrating AI across SAP learning ecosystems to foster continuous, personalized development.