The increasing use of composite materials in sectors like automotive and aerospace poses serious problems for preserving their material performance and integrity. Because they provide automated, accurate, and effective inspection capabilities, advanced inspection techniques—in particular, robotic intelligence technologies—have emerged as viable options. This paper provides a comprehensive review of the key robotic intelligence technologies used in the inspection of composite materials, highlighting advancements in vision-based, tactile-based, and force-based traditional approaches, as well as the development in modern advanced deep learning methods such as Convolutional Neural Network (CNN) based image processing techniques for inspection. In order to guarantee accurate and steady manipulation during inspection jobs, robot control strategies are also investigated. The robot’s capacity to navigate intricate composite constructions while preserving constant inspection quality has also been greatly improved by the use of clever path-planning algorithms. The paper concludes by outlining future directions for improving inspection accuracy and efficiency through AI integration and advanced sensor technologies.