Teaching in higher education is becoming increasingly complex due to expanding content requirements and rising expectations. The flipped classroom model, which emphasizes student engagement and deeper learning, places additional demands on educators to prepare accurate, self-contained study materials suitable for independent learning. This study explores the potential of generative AI tools to streamline the material preparation process in flipped classroom settings, particularly in informatics and statistics courses. A qualitative approach is adopted, based on the real teaching practices of university educators who integrated AI tools into various stages of lesson preparation, including content generation, terminology simplification, and development of quizzes and summaries. Time spent on different preparation phases, with and without AI support is measured, and t-tests are used to assess the statistical significance of observed time savings, with R as the analytical tool.