This paper explores how Generative Artificial Intelligence (AI) enhances personalized learning by dynamically adjusting content, providing immediate feedback, and tailoring educational pathways. Although personalized education is increasingly essential, traditional methods often overlook individual learner differences. Current research largely focuses on AI-driven content generation, overlooking the creation of adaptive learning experiences responsive to evolving learner needs. This study aims to address this gap by examining how Generative AI’s adaptability, feedback, and personalization capabilities influence perceived learning efficiency among learners in both higher education and corporate training contexts. Drawing from Technology Acceptance Model (TAM) and Task-Technology Fit (TTF) frameworks, the research also explores how prior AI experience moderates these relationships. Results could inform adaptive curricula and training programs, improve educational outcomes, enhance workforce readiness, and foster inclusive learning opportunities across diverse learner populations.