ChatGPT by OpenAI, a large language model, offers innovative potential for writing and optimizing SQL queries, combining speed, consistency, and a vast knowledge base of SQL functions and best practices. It functions as a valuable tool for both novice and seasoned analysts by generating SQL queries quickly, serving as a learning resource, and aiding in brainstorming unfamiliar query structures. Despite its advantages, such as adaptability to different SQL flavors and aiding in rapid development, ChatGPT has limitations, including a lack of deep contextual understanding, the need for specific instructions, and potential security concerns when sharing sensitive data. While it complements human analysts by handling repetitive tasks and providing optimization suggestions, it cannot fully replace the nuanced expertise and intuition of experienced professionals, especially in complex, performance-critical scenarios. Tools like PopSQL further enhance this integration by embedding AI capabilities directly into SQL workflows, facilitating context-aware interactions and error corrections. As AI intertwines with SQL, embracing its capabilities while acknowledging its limits can lead to more efficient and effective SQL development.