The conversational queries powering agentic commerce are more expensive than traditional keyword searches. For this technology to be profitable for retailers, it must generate new sales that wouldn't have otherwise happened, rather than simply cannibalizing existing purchase channels.
Many e-commerce platforms derive most of their profit from on-site advertising. AI agents, expected by users to provide unbiased, optimal results, conflict with this "pay-for-placement" model, creating a significant risk to existing revenue streams that fund marketplace operations.
While external AI agents pose a long-term threat, established retailers can lead in the initial phase of agentic commerce. They control crucial assets like purchase history, payment information, and—most importantly—customer trust, which are essential for driving early adoption of on-site AI assistants.
While consumers increasingly use AI for top-of-funnel tasks like search and discovery, a significant trust gap prevents them from handing over full control for end-to-end purchasing. This barrier dictates the pace of adoption, with most activity remaining in the 'AI-assisted' rather than 'fully autonomous' stage.