{"slug": "agentic-share-of-search-a-multi-agent-ai-system-for-competitive-decision-making", "title": "Agentic Share-of-Search: A Multi-Agent AI System for Competitive Decision-Making in LLM-Mediated E-Commerce", "summary": "A multi-agent AI system called Agentic Share-of-Search (ASoS) automates competitive visibility measurement and root-cause diagnosis in LLM-mediated e-commerce, according to an arXiv cs.AI paper by Spandan Ghose Chowdhury. The system deploys query agents across leading AI platforms and uses a ReAct-based diagnostic agent to recommend prioritized merchandising interventions. A 100-trial ablation study found the agent recovered the ablated signal in 39% of trials (95% CI: 30.0% - 48.8%, 5.5x over chance), rising to 63.9% among high-correlation ablations.", "body_md": "# Agentic Share-of-Search: A Multi-Agent AI System for Competitive Decision-Making in LLM-Mediated E-Commerce\n\nBy Spandan Ghose ChowdhurySource: \n\n[arXiv cs.AI](https://arxiv.org/list/cs.AI/recent)\narXiv:2609.11190v1 Announce Type: new \nAbstract: AI shopping assistants increasingly redirect consumer discovery, creating an urgent need for tools that support seller-side competitive decision-making. We present a multi-agent AI system that automates competitive visibility measurement and root cause diagnosis in \n\n[LLM](/glossary/llm)-mediated ecommerce. The system introduces Agentic Share-of-Search (ASoS) as the decision target, deploys query agents across leading AI platforms, and uses a ReAct-based diagnostic agent to recommend prioritized merchandising interventions. A 100-trial ablation study, presented as a feasibility[evaluation](/glossary/evaluation)of this prototype, shows the agent recovers the ablated signal in 39% of trials (95% CI: 30.0% - 48.8%, 5.5x over chance), rising to 63.9% among high-correlation ablations.\nGet AI news in your inbox\n\nDaily digest of what matters in AI.", "url": "https://wpnews.pro/news/agentic-share-of-search-a-multi-agent-ai-system-for-competitive-decision-making", "canonical_source": "https://www.machinebrief.com/news/agentic-share-of-search-a-multi-agent-ai-system-for-competit-32ys", "published_at": "2026-09-12 04:00:00+00:00", "updated_at": "2026-09-12 05:27:44.985006+00:00", "lang": "en", "topics": ["ai-agents", "large-language-models", "ai-research", "ai-products"], "entities": ["Agentic Share-of-Search", "Spandan Ghose Chowdhury", "arXiv cs.AI", "ReAct"], "alternates": {"html": "https://wpnews.pro/news/agentic-share-of-search-a-multi-agent-ai-system-for-competitive-decision-making", "markdown": "https://wpnews.pro/news/agentic-share-of-search-a-multi-agent-ai-system-for-competitive-decision-making.md", "text": "https://wpnews.pro/news/agentic-share-of-search-a-multi-agent-ai-system-for-competitive-decision-making.txt", "jsonld": "https://wpnews.pro/news/agentic-share-of-search-a-multi-agent-ai-system-for-competitive-decision-making.jsonld"}}