The study explores the application of generative models in creating website content optimised for search engines and evaluates their effectiveness compared to human-generated content. The paper begins by introducing the search engine and SEO issues, followed by a discussion of the generative models employed in the experiment, specifically ChatGPT and DALL·E. The primary focus lies in the presentation of the research methodology, which includes an original approach to designing the experiment for website content evaluation. Furthermore, the paper introduces a novel indicator for measuring SEO effectiveness in terms of website visibility in search engine results. The results of the study compare the performance of three website versions, one of which featured content generated by AI models. Additionally, a survey was conducted to assess the quality of the content from the perspective of users. The findings indicate that content created by a professional human copywriter consistently outperformed generative model-based content in both SEO metrics and user quality evaluations. These results highlight the limitations of current generative models in replicating the nuanced expertise of human professionals in the context of SEO-driven content creation. These findings point to a broad field of research into the quality of content produced by generative models.