Retailers Are Making a Risky Bet on Agentic AI That Could Cost Them Their Customer Relationships

By Hector Herrera | May 4, 2026 | Vertical: Retail | Type: Vertical Article

Retailers racing to deploy agentic AI — autonomous AI systems that browse, compare, and buy on behalf of consumers — risk handing over the most valuable asset in retail: the direct relationship with the customer. A Retail Dive analysis published this week lays out the structural problem clearly: when Amazon or Walmart controls the AI agent that decides what a consumer discovers and buys, every other retailer becomes a supplier in someone else's ecosystem.

This is not a distant risk. It is the business model already being built.

The Agentic Commerce Shift

Agentic AI (AI systems authorized to take actions autonomously on a user's behalf) is moving from novelty to infrastructure in retail. Consumers are already using AI assistants to research purchases, compare prices, and in some cases, complete transactions automatically. The question is whose AI agent they're using — and which retailer's data feeds into that agent's recommendations.

Amazon's AI shopping layer has first-party access to its own product catalog, customer purchase history, and behavioral signals. When an Amazon AI agent recommends a product, Amazon captures the conversion, the data, and the customer relationship. A mid-market retailer whose products appear in that agent's results is just a fulfillment node.

Walmart is building the same infrastructure. Both companies are explicitly positioning their AI commerce layers as the default consumer interface — the starting point for discovery before a brand or product is ever considered.

The Data Problem

What makes this dynamic structurally dangerous for independent retailers is not just the revenue impact — it's the data starvation it creates.

Direct-to-consumer retail relationships generate first-party data: purchase patterns, browsing behavior, preferences, and customer-service interactions. That data feeds product development, inventory planning, personalization, and marketing. When a customer buys through an AI agent hosted on Amazon or Walmart's platform, that behavioral data stays with the platform.

Over time, a retailer whose customers route through someone else's AI layer becomes progressively worse at understanding its own customers. The data gap compounds. The personalization gets weaker. The AI capabilities fall further behind.

Who Is Vulnerable

The retailers most exposed to this dynamic are in the middle: brands large enough to have invested in e-commerce infrastructure but not large enough to build a first-party AI commerce layer with genuine consumer adoption.

Luxury brands and niche specialists have some protection — their customers seek them out directly, and brand identity provides a reason to bypass a generic AI agent's recommendation. Commodity retailers at the low end are already largely competing on price in marketplaces and have less to lose.

The risk is concentrated in mid-market brands that have built genuine customer loyalty through service, selection, or product quality — but now face the prospect of that loyalty being routed through a platform AI that doesn't distinguish between them and a lower-margin substitute.

What Retailers Can Actually Do

The retailers navigating this most intelligently are doing two things simultaneously:

1. Building their own AI touchpoints. Personalization tools, shopping assistants, and AI-powered customer service that keep the interaction on the retailer's own platform. This requires real investment, and the gap between what a mid-market brand can build versus what Amazon can build is large — but maintaining any direct channel is better than surrendering all of them.

2. Treating first-party data as a strategic asset, not just a marketing input. Loyalty programs, email lists, account creation incentives, and post-purchase engagement all generate the data that keeps the direct relationship alive even as AI intermediaries proliferate.

Neither approach fully solves the problem. But the retailers that treat agentic AI as a channel management challenge — rather than just an efficiency opportunity — are the ones most likely to maintain brand relevance over the next five years.

What to Watch

Watch how Amazon and Walmart's AI shopping products evolve. Specifically: do they allow third-party brands to influence recommendations, build brand presence, or access aggregate behavioral data? The terms they set for retailer participation in their AI commerce layers will determine whether mid-market retail has a viable path forward — or becomes structurally dependent on platforms they cannot control.