Despite its advantages, AI in protecting trademarks, monitoring and enforcement has accuracy and reliability concerns. One of the primary challenges is the potential for false positives and negatives. False positives can lead to unnecessary legal actions against entities not infringing on trademarks, while false negatives may result in undetected infringements. The effectiveness of AI systems heavily depends on the quality of the data they are trained on and the robustness of their algorithms.