This study provides a comprehensive analysis of the application of artificial intelligence (AI) in kidney disease research, highlighting key trends, collaborative networks, and research hotspots. A bibliometric analysis of 631 articles published between 2012 and November 2023 revealed a significant exponential growth in AI-related publications in kidney disease research. Nephrology Dialysis Transplantation was the leading publisher, followed by the American Journal of Transplantation and Scientific Reports. The United States, China, and India were the top contributors, accounting for 25.99%, 24.72%, and 9.83% of the articles, respectively. Major institutions such as Mayo Clinic, Harvard University, and Sun Yat-Sen University were also prominent contributors. The study identified key research topics, including machine learning, deep learning, and predictive modeling, and highlighted the importance of AI in early detection and management of kidney diseases. The analysis also revealed that AI has the potential to improve diagnostic accuracy, facilitate early interventions, and enhance patient outcomes. However, challenges such as data privacy, ethical considerations, and the need for collaboration between healthcare professionals and AI systems remain. The study emphasizes the importance of developing robust AI tools that are accurate, transparent, and ethically sound. Future research should focus on addressing these challenges and exploring the potential of AI in improving kidney disease care. The findings of this study provide valuable insights into the current state of AI research in kidney disease and offer a foundation for future research directions.This study provides a comprehensive analysis of the application of artificial intelligence (AI) in kidney disease research, highlighting key trends, collaborative networks, and research hotspots. A bibliometric analysis of 631 articles published between 2012 and November 2023 revealed a significant exponential growth in AI-related publications in kidney disease research. Nephrology Dialysis Transplantation was the leading publisher, followed by the American Journal of Transplantation and Scientific Reports. The United States, China, and India were the top contributors, accounting for 25.99%, 24.72%, and 9.83% of the articles, respectively. Major institutions such as Mayo Clinic, Harvard University, and Sun Yat-Sen University were also prominent contributors. The study identified key research topics, including machine learning, deep learning, and predictive modeling, and highlighted the importance of AI in early detection and management of kidney diseases. The analysis also revealed that AI has the potential to improve diagnostic accuracy, facilitate early interventions, and enhance patient outcomes. However, challenges such as data privacy, ethical considerations, and the need for collaboration between healthcare professionals and AI systems remain. The study emphasizes the importance of developing robust AI tools that are accurate, transparent, and ethically sound. Future research should focus on addressing these challenges and exploring the potential of AI in improving kidney disease care. The findings of this study provide valuable insights into the current state of AI research in kidney disease and offer a foundation for future research directions.