Transformation of Search Engine Optimization Strategies from Keyword-Based to Search Intent Approaches in the Era of Generative AI: A Scoping Review and a Framework for Measuring Visibility in Answer Engines

Generative artificial intelligence (AI) is changing web search from ranked lists of links into synthesised, cited answers, which weakens search engine optimization (SEO) practices built on keyword density and raises the question of how visibility should be measured. This study maps how SEO strategy has moved from keyword-based to search-intent approaches, identifies the influence of generative AI on SEO practice, and proposes a framework for measuring visibility in answer engines. A scoping review was conducted following the PRISMA ScR guidance, with explicit eligibility criteria based on the Population-Concept-Context framework and a PRISMA-style flow of records. From 44 records, 27 sources were included: 25 peer-reviewed journal articles, conference papers, and book chapters, and two working papers that are used only as supplementary evidence and are accompanied by explicit risk parameters. Fifteen sources were published between 2024 and 2026. Four findings emerge. First, SEO has evolved through three phases, namely keyword-based, intent-based, and generative, in which the unit of optimisation shifts from keywords to user needs and then to information worth citing. Second, evidence indicates that extractable evidence such as citations, quotations, and statistics improves visibility in generative engines, whereas keyword stuffing does not. Third, answer engines show weaknesses in citation accuracy, source concentration, and market bias, and early field evidence reports fewer outbound clicks when AI summaries appear. Fourth, because click-through rate alone cannot capture visibility in answer engines, the study proposes a five-stage framework that combines LLM Citation Rate, Brand Mention Frequency, Share of Model, and Entity Association Strength with traditional traffic indicators. The framework is conceptual and requires empirical validation, particularly in Indonesian-language contexts.

Search Engine Optimization, Search Intent, Generative AI, Generative Engine Optimization, Digital Marketing

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