Published February 8, 2026 | Version v1
Preprint Open

AI Engine Optimization (AIEO). Comparative taxonomy of Search Engine Ranking techniques SEO, AEO, GEO and AGO in Large Language Models

Authors/Creators

  • 1. ROR icon IE University
  • 2. ROR icon Universidad Monteávila

Description

The architecture of information retrieval on the global web is undergoing a radical transformation: a shift from lexical document retrieval (Information Retrieval) to generative inference. The traditional paradigm of search directory positioning is giving way to conversational interfaces and autonomous agents. The following technical essay explains AI Engine Optimization (AIEO) as a unifying discipline that integrates search engine optimization (SEO), semantic structuring (AEO), generative models (GEO), and brand influence in latent spaces (AGO).

The study employs a longitudinal, mixed-methods design combining participant observation and multiple case studies, drawing on professional experience from 18 years of SEO practice, during which 417 projects were completed (N=417). Meanwhile, the study was triangulated with 50 market intelligence data points collected during academic training studies at IE Business School and the Catholic University of San Antonio of Murcia, and continuing training from 2022 to 2026.

Keywords: Natural Language Processing, SEO, GEO, Generative Engine Optimization, Deep, Data Analytics.

1. The collapse of traditional search

Currently, the digital industry encounters a paradox of diminishing returns: while content production capacity increases, organic visibility decreases. Market data confirm the new trend: Gartner (2024) projects a 25% decline in traditional search volume by 2026, while SparkToro (2024) reports that 58.5% of Google searches end without a click to an external website (Zero-Click).

Meanwhile, Microsoft Advertising (2024) indicates that 41% of users prefer a direct, summarized answer to a list of links. The new direction in the Search Marketing phenomenon necessitates an ontological redefinition of digital success, as the new objective is to generate inferences rather than simply capture a visit. A modern shift requires a brand to become the "Source of Truth" on which the Artificial Intelligence (AI) model relies to generate its responses.

Given a new scenario, isolated disciplines are insufficient, as the optimization industry requires a unified taxonomy that addresses the complexity of Large Language Models (LLMs).

Isaías Blanco - Natural Language Processing & Deep Learning Specialist

Files

Isaías Blanco - AI Engine Optimization (AIEO).pdf

Files (519.1 kB)

Additional details

Dates

Available
2026-02-08
Final version

Software

Repository URL
https://github.com/isaiasblancoai/researchlab
Programming language
Markdown , Python , HTML+PHP , CSS , JavaScript
Development Status
Active

References

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  • Fishkin, R. (2024). The 2024 Zero-Click Search Study. SparkToro.
  • Gartner. (2024). Gartner Predicts Search Engine Volume Will Drop 25% by 2026. Gartner Press Release
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  • Zhang, Y., et al. (2023). Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models. Tencent AI Lab