The limitations of current AI technologies include challenges related to data dependency, lack of common sense understanding, and biases within algorithms. AI models often require extensive curated datasets to function effectively, which may not always be available or representative. Additionally, while AI can perform specific tasks with remarkable accuracy, it lacks broader contextual awareness and reasoning capabilities akin to human intuition. Furthermore, biases present in training data can lead to skewed outcomes, raising ethical concerns. These limitations highlight the importance of cautious deployment and continuous improvement in AI development.