This study was conducted with the aim of qualitatively examining and comparing the performance of several AI-based tools in teaching the concepts of variance and standard deviation, using a qualitative approach and case study method. The statistical population consisted of AI-based tools applicable in statistics education. Sampling was purposeful, based on accessibility and the ability to generate statistical content, and five tools—Gemini, ChatGPT, MathGPT, MagicSchool, and DeepSeek—were selected. Data were collected using four input prompts, and to evaluate the AI responses to these prompts, criteria such as clarity, engagement, structure, interactivity, real-world relevance, and appropriateness for students were employed. Data analysis was performed through coding with the assistance of MAXQDA software, and the reliability of the analyses was confirmed with a kappa coefficient of 0.8. The findings indicated that AI tools can enhance statistics learning by providing engaging and real-world-relevant content, though they have limitations such as lack of creativity or insufficient accuracy. Overall, in this domain, the tools exhibited varying performance. Gemini and DeepSeek performed relatively better in delivering precise and coherent lesson plans, ChatGPT in designing analytical questions and attractive visual images, MagicSchool in facilitating group activities and addressing common errors, and MathGPT in providing comprehensible content related to the concepts of variance and standard deviation. Combining these tools with teacher supervision—which is essential for maintaining academic integrity—can strengthen statistical literacy and critical thinking, preparing students to face the challenges of a data-driven world.