The advancement of generative models in simulating human creativity has greatly impacted the art world. In this context, artists are concerned about the devaluation of their work, especially considering the questions that appear surrounding authenticity and ownership rights. This study uses DE-FAKE, a state-of-the-art research-based detection tool, to address the crucial problem of separating AI-generated art from human-created works. The performance of DE-FAKE across a wide range of artistic styles will be assessed by carefully examining images chosen from the reputed WikiArt and AI-ArtBench datasets. This serves to highlight the advantages and disadvantages of the system. While DE-FAKE performs well in recognizing AI-generated art in the modern and abstract domains, the results show that it faces significant difficulties in recognizing more realistic styles, highlighting the need for additional development. This study lays a solid foundation for future research and practical solutions for safeguarding artists’ intellectual property in the era of AI-generated art.