The rising demand for high-quality, timely content for online and blended learning environments presents significant challenges for instructional designers, particularly in managing resource-intensive tasks such as video production and image sourcing. This study investigates the impact of using artificial intelligence (AI), specifically large language models (LLMs), on key evaluation criteria for self-organized, online, and blended learning modules. Using the case of 'aprendo. ch,' a professional development platform provided free of charge to teachers in the canton of St. Gallen that has recently implemented AI-enhanced workflows, we analyze how AI-enhanced content affects module evaluation outcomes, including perceived learning quality, learner satisfaction, and instructional design efficiency. Statistical analyses indicate significant differences between AI-enhanced and traditional modules, with AI-enhanced modules receiving higher evaluations in module structure, competency development, and learner recommendation. Furthermore, we discuss ethical considerations, such as data bias and content accuracy, and provide practical recommendations for the responsible integration of AI in educational design to balance efficiency with educational quality.