Companies and stores have historically crafted online sales plans to draw shoppers onto sites via search results, ads, and immersive digital experiences. Yet, as AI grows, purchases are often finalized before a user even visits a site.
This shift is reflected in the decline in organic traffic from search engines, as consumers are now asking AI assistants for recommendations rather than simply browsing category pages. AI agents will also compare products and, in some cases, complete purchases on consumers’ behalf.
Changing Commerce Strategies
As a result, brands and retailers are now competing not only to rank in search results but also to have their products understood and recommended by AI. They need to think beyond SEO and focus on making their product data complete, structured, trusted, and machine-readable.
AI can only recommend what it can confidently understand, making product data an essential aspect of commerce. Brands and retailers must ensure their product information is accurate, consistent, and complete to remain competitive in an AI-driven marketplace.
Agentic Gap and Data Readiness
Romain Fouache, CEO of Akeneo, notes that there is no good AI without good data. The biggest mistakes brands and retailers make when adopting AI are related to data readiness, including inconsistent or incomplete product information.
To close the agentic gap, businesses need a single source of truth, clear ownership of product data, and consistent processes. With a solid data foundation in place, they can use AI to centralize, enrich, activate, and optimize product information with confidence.
Product Data as a Strategic Asset
Product data is now at the heart of discoverability, customer confidence, conversion, pricing decisions, merchandising, and AI recommendations. Rich, contextual product information helps customers make better decisions and gives AI the confidence to understand and recommend products.
As AI-driven commerce continues to evolve, product data will become an even more critical commercial asset. Businesses that prioritize product data and connect it with pricing and commercial intelligence will have a significant competitive advantage in the future.
The role of product teams will also change, as they will be responsible for revenue generation and ensuring products are discoverable, trusted, and commercially successful across every channel, including AI-powered experiences.
