The Android permission system regulates access to sensitive mobile device resources and data, such as camera and location. To access these resources, third-party application (app) developers need to request permissions. However, the Android permission system is complex and fast-evolving, presenting developers with numerous challenges surrounding compatibility issues, misuse of permissions, and vulnerabilities related to permissions. Our study aims to explore whether Large Language Models (LLMs) can serve as a reliable tool to assist developers in using Android permissions correctly and securely, thereby reducing the risks of misuse and security vulnerabilities in apps. In our study, we analyzed 1,008 Stack Overflow questions related to Android permissions and their accepted answers. In parallel, we generate answers to these questions using a popular LLM tool, ChatGPT. In our evaluation, we focus on how well the AI-generated responses align with the accepted answers provided by developers on Stack Overflow. Our findings show that above 50% of ChatGPT-provided answers align with Stack Overflow’s accepted answers. ChatGPT offers better-aligned responses for challenges related to Documentation and Conceptual Understanding, while it provides less aligned answers for Debugging-related issues. In addition, we found that ChatGPT provides more consistent answers for Documentation and Conceptual Understanding, while Implementation-related answers are the least consistent. Our study demonstrates the potential for using LLMs such as ChatGPT as a supporting tool to help developers navigate Android permission-related problems.