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AI PERCEPTION INDEX 2026: How Large Language Models Position Brands in the AI Era

  • Zenodo (CERN European Organization for Nuclear Research)
  • European Organization for Nuclear Research
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Abstract

This report introduces the AI Perception Index (MPI), a composite scoring framework developed by ARGEO AI to measure how large language models (LLMs) understand, represent, and position brands in AI-generated responses. Unlike traditional brand monitoring tools that track mentions or sentiment, the MPI evaluates the quality, authority, and consistency of AI-generated brand representation across multiple dimensions: Surface Presence Index (SPI), Semantic Composite (SC), Competitive Dominance Ratio (CDR), and Cross-Model Drift. The 2026 index benchmarks 15 brands across five sectors — AI tools, CRM platforms, marketing automation, analytics, and e-commerce — using structured query protocols applied to GPT-4o and Claude Sonnet 3.7. Key findings reveal significant cross-model perception drift, the disconnect between surface mention frequency and semantic authority, and the emergence of Perception Control as a distinct strategic discipline beyond Generative Engine Optimization (GEO). This work establishes a foundational measurement methodology for AI brand perception and introduces ARGEO AI's Perception Control framework as the strategic response to the challenges of brand representation in the AI era. Published by ARGEO AI, Antalya, Turkey. https://argeo.ai

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Publication details

DOI
10.5281/zenodo.18993806
OpenAlex
W7135195967
Document type
preprint
Language
EN
Source
Zenodo (CERN European Organization for Nuclear Research)
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