The article analyzes how the rapid development of artificial intelligence has gradually changed Google search and, accordingly, the logic of SEO. The evolution of approaches to ranking was described. Starting from early mechanisms, where links and page authority (PageRank) played a key role, to modern models that try to “understand” the content of the query, context and user intent. The article explained that SEO is gradually changing and instead of “technical tricks” under algorithm signals, high-quality content, clear structure, real benefit for the reader and trust in the source are becoming the main ones. Generative changes in the issue were also considered - SGE and AI Overviews - when Google does not just show links, but increasingly forms a ready-made short answer right on the results page (SERP). In addition, the available data and observations on the impact of AI Overviews on the clickability of organic results, the growth of the share of “zero-click” interactions and changing user behavioral scenarios are summarized. It is also described how in such conditions the need for approaches such as Generative Engine Optimization is formed, where it is important not only to "be in the top", but also to get to the sources on which the generated answer is based. In addition, the article highlights the risks associated with generative content in search: possible errors and "hallucinations", the difficulty of quick fact-checking, as well as the blurring of responsibility between the platform, content authors and the audience. It was also substantiated the need to adapt the digital competencies of specialists to the conditions when classic search is increasingly transformed into a dialogue with large language models, and the competitiveness of content is determined by its structure, transparency of sources and compliance with EEAT principles. As a result, the work describes the transition of search to a model where the answer becomes a product, and quality, transparency and trust are key factors for both users and site owners. The study is based on a review of scientific publications and technical materials of Google, as well as on the analysis of data already collected from SEO platforms. The results obtained outline the cause-and-effect relationships between the stages of algorithm development and optimization practices and form the requirements for business content strategies in the reality of generative search.
Kyryl Dubinin (Thu,) studied this question.