Who Owns the AI Recommendation? A Multi-Industry Empirical Map of Brand Category Ownership Across Large Language Models

This study presents an empirical analysis of brand category ownership in AI-generated recommendations across three large language models: GPT-5.2, Google Gemini 3 Flash, and Perplexity sonar-pro. Utilizing 3,750 responses across 50 brands and 250 queries, the authors introduce three metrics—Category Ownership Index (COI), Competitive Vacuum Index (CVI), and Displacement Score (DS)—to assess brand recommendation concentration, finding a moderate Gini coefficient of 0.28 and cross-model agreement of 41.6% on top recommendations. These insights challenge the prevailing winner-takes-all narrative in AI recommendations, providing practitioners with a framework for competitive intelligence analysis in brand positioning.