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GEO: Influencing Commerce, Human Decision Making, and Global Policy Through Generative Information Engines

Authors: Mohanty, Gokul; Marutheesh, Eshaan;

GEO: Influencing Commerce, Human Decision Making, and Global Policy Through Generative Information Engines

Abstract

The transition from traditional search engines to Generative Information Engines (GIEs) is fundamentally reshaping how information is accessed, interpreted, and acted upon. Unlike ranking-based systems, GIEs synthesize responses that include a limited set of entities, making inclusion and representation the primary determinants of visibility and influence. This paper introduces Generative Engine Optimization (GEO) as the strategic framework required to navigate this shift, supported by core constructs including the AI Visibility Index (AIVI), AI Reputation Score (AIRS), and Distributed Authority Domain Placement (DADP). We demonstrate how these mechanisms collectively influence commercial outcomes, institutional legitimacy, and human decision-making by controlling which entities are surfaced and how they are framed. As generative systems increasingly mediate global decision processes, entities that fail to adopt GEO risk structural invisibility and decline, while those that do gain the ability to shape markets, policy, and human behavior at scale.

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