AI Roundtable: Why Your AI Strategy Will Live or Die on Retrieval
Every CTO is being asked about their AI strategy.
Most organizations focus on models, infrastructure, and prompts. But there's a critical capability that determines success or failure: information retrieval.
Your competitive moat in AI isn't the LLM and prompts you choose—it's your proprietary data. But if your AI systems can't accurately find and surface the right information, you're building on sand.
Industry experts suggest that 90%+ of RAG (retrieval augmented generation) failures stem from poor retrieval, as opposed to models and prompts. Yet, most organizations treat search as a solved problem or a "vector database" checkbox.
Implementing good data-driven evaluations into your projects will show you that it’s not. This isn't just technical—it's strategic. While LLMs commoditize AI capabilities, retrieval quality over your unique data is where differentiation happens. Organizations that master this create AI systems that understand their business. Those that don't get hallucinating chatbots and blind agents.
We'll cover:
-Why retrieval is a critical bottleneck, the gap between "vectors in a database" and production systems, and how to build retrieval as a core competency.
-If AI is strategic to your business, retrieval expertise needs to become a first-class AI capability in your organization.
Your host:
TREY GRAINGER is author of the book AI-Powered Search and is the founder of Searchkernel, a software consultancy building the next generation of AI search. He is an advisor to several startups and adjunct professor of computer science at Furman University. He previously served as CTO of Presearch, a decentralized web search engine, and as chief algorithms officer and SVP of engineering at Lucidworks, a search company whose technology powers hundreds of the Fortune 1000. Trey also teaches hands-on courses like "AI-Powered Search: Modern Retrieval for Humans and Agents" to help organizations improve their AI systems.