Generative AI tools are transforming library cataloging by improving efficiency and expanding access to multilingual resources. This study examines the application of AI in automating the transliteration of Wade-Giles romanized titles into Pinyin in MARC records. Three generative AI tools—ChatGPT, Copilot, and Gemini—were evaluated for their efficiency, and they exhibited distinct strengths and limitations. The study highlights persistent challenges, including inconsistent outputs, fluctuating accuracy levels, and the need for data pre-processing. These findings paint a promising future for AI integration in cataloging workflows but also highlight the need for continuous refinement to achieve scalable performance optimization.