A new era of Agentic Commerce is unfolding as autonomous AI agents handle purchasing tasks—price comparisons, review analysis, availability checks, and decision execution—on users’ behalf.

Brand and marketing are shifting from emotional loyalty to data-driven decisions, with algorithms weighing availability, reputation, features, reviews, and efficiency, potentially reducing traditional marketing signals' influence.

Amazon’s Rufus example points to market direction: hundreds of millions of users, over $10 billion in annualized incremental revenue, and markedly higher conversion rates, driven by structured data, APIs, and algorithmic advertising.

Momentum is global: hundreds of millions of weekly ChatGPT users and billions in AI-enabled system use monthly, with AI-driven e-commerce traffic surging during holidays and Gartner forecasting AI agents managing up to trillions in B2B operations by 2028.

Brands must answer a critical question as machines buy: how to appeal to non-human decision-makers and ensure product readability so AI marketplaces can surface and recommend their offerings.

The shift toward autonomous purchasing is accelerating and represents a structural change in e-commerce, with broad implications for marketing, data needs, and business strategy.

A new concept—Agent Engine Optimization (AEO)—emerges, prioritizing machine-readability and structured data so AI agents can interpret product attributes, availability, and reputation.

AI adoption is widespread beyond tech hubs: in Spain, 13% of consumers use AI tools for purchases, and about one in three used conversational systems to compare prices during Black Friday.