This paper examines the efficiency of artificial intelligence (AI)-supported patent analytics tools in detecting relevant prior art associated with a specific patent. Our research demonstrates that AI-supported prior art search yields results more rapidly; these results are visually sorted in a transparent manner, presenting titles, abstracts, and images, which facilitates swift decision-making regarding the relevant state of the art. The majority of the results proposed by intellectual property (IP) tools were very broadly connected to the presented invention, but the correlation with patents recognized as relevant by the patent examiner and inventor was weak. Significant differences were observed between tools. Although our initial assumption was that IP tools should provide similar results if data coverage is identical, our research findings do not support it. However, AI-supported IP analytics tools develop progressively and in the next few years, they will certainly successfully complement or even displace traditional prior art searching.