Positioning SEO in the Research Field of AI in Web Search: A Bibliometric Analysis and Agenda for Future Research

Web search is a primary gateway for accessing digital information, and artificial intelligence (AI) fundamentally reshapes both search infrastructure and search engine optimization (SEO) practices through which organizations achieve online visibility. Despite this dual transformation, no study has systematically mapped the position of SEO research within this field. This study addresses this gap through keyword co-occurrence analysis of 2273 publications from Scopus, Web of Science, and IEEE Xplore (2015–2025). The analysis identifies five thematic clusters that overlap in temporal regards and represent the technical aspects by spanning retrieval, semantic processing, knowledge extraction, and large language model-based architectures, concluding in conversational search. However, SEO-specific practice-oriented terminology remains sparse and confined to a single cluster. Building on these findings, the study develops a research agenda comprising seven research questions across three directions: evaluating AI-adapted SEO strategies and optimization for generative search, conceptualizing visibility under AI-mediated search, and examining stakeholder adaptation and value distribution within the search ecosystem. These findings provide a foundation for future research addressing the growing gap between the field’s technical and SEO-specific dimensions.