Artificial intelligence content detection techniques using watermarking: A survey

The rapid advancement in AI-generated content has catalyzed artistic creation, advertising, and media dissemination. Despite their widespread applications across several domains, AI-generated content inherently poses risks of identity fraud, copyright violation and unauthorized use. Watermarking has emerged as a critical tool for copyright protection, allowing embedding of identification information in AI-generated content, and enhances traceability and verification without hurting user experience. In this study, we provide a systematic literature review of the technique for detecting AI content, especially text and images, using watermarking, spanning studies from 2010 to 2025. Studies included in this review were peer-reviewed articles that applied watermarking to effectively distinguish AI-generated content from real or human-written content. We report strong past and current approaches to detecting watermarking-based AI content, especially text and images. This includes an analysis of how watermarking methods are used on AI-generated content, their role in enhancing performance, and a detail comparative analysis of notable techniques. Furthermore, we discuss how these methods have been evaluated, identify the research gaps and potential solutions. Our findings provide valuable insights for future watermarking-based AI content detection researchers, applications and organizations seeking to implement watermarking solutions in potential applications. To the best of our knowledge, we are the first to explore the detection of AI content, especially text and image, detection using watermarking.