This is about search moving from “blue links on Google” to AI helpers that immediately show the right product, store, or app—no scrolling, no guessing. Think of it as your own smart shopper that understands what you want, where you are, and what device you’re on, then jumps straight to the best answer or product.
Traditional SEO assumes people type keywords into Google and click links. AI search changes the game: queries become conversational, spread across many platforms (chatbots, social, app stores, voice), and users expect direct answers instead of link lists. Businesses that only optimize for classic SEO risk disappearing from customer journeys as search traffic and ad dollars shift into AI-driven results and closed ecosystems.
Defensibility will come from proprietary intent and behavior data (how users search and convert across channels), deep integration with AI search platforms (GEO, ASO, in-app and conversational agents), and owning high-intent categories or brands that AI systems are biased to recommend due to historical performance and user trust.
Hybrid
Vector Search
Medium (Integration logic)
Context window cost and latency for AI-powered search interactions at scale, plus reliable freshness of product and inventory data across many discovery surfaces.
Early Majority
This use case frames AI search not just as ‘better SEO’ but as a $750B macro shift from keyword-based web search to multi-surface discovery (GEO, ASO, conversational and in-app AI). The differentiated angle is treating AI search as an omnichannel demand-redistribution problem for ecommerce and digital products, rather than a narrow ranking or ad-optimization tweak.