Agentic Commerce: How AI Shopping Agents Are Reshaping Retail Decisions

Agentic commerce, which involves AI-powered shopping agents making purchase decisions, is emerging as a significant force in the retail sector. Discussions with CEOs, board members, investors, and operating teams across various markets indicate a universal interest in understanding and competing in this evolving environment.

Unlike traditional shopping, agentic commerce means an AI agent will assemble a shopping basket and select retailers based on predefined constraints such as price, availability, loyalty value, and delivery speed. This shift means the agent, rather than the customer, will determine which retailers are deemed most suitable for a transaction.

While fully autonomous shopping agents are still developing, early patterns are visible. Current fulfillment platforms already evaluate retailers based on metrics like availability, substitution rates, and delivery reliability. As agentic commerce matures, the scope and autonomy of these evaluations will expand, making foundational decisions about data structure, decision governance, and platform partnerships crucial for retailers looking to compete on their own terms.

Operational excellence is identified as an entry requirement for success in this new paradigm. Insights from one of the largest retail data science organizations, 84.51°, suggest that agentic AI creates significant value in back-office operations, innovation pipelines, and connecting data to decisions at scale. For instance, in food manufacturing, an agentic system can optimize product formulation across taste, quality, shelf life, margin, and production feasibility, simulating scenarios much faster than human teams.

Fragmented or inconsistently executed internal operations, such as fill rates or handling exceptions, can lead agentic systems to route demand to other retailers. The risk of customer disintermediation, where the agentic platform becomes the primary interface and the retailer merely an inventory source, is substantial. This mirrors previous shifts in the financial services industry, where algorithmic tools inserted themselves between firms and clients.

To mitigate these risks, retailers need full visibility into how they are ranked by agents and the signals platforms are using. Strategic negotiation of platform deals, including data rights, is advised before dependency on these platforms becomes entrenched. The focus should be on demonstrating unique value propositions. Ultimately, agentic commerce will favor retailers that can deliver the right product at the right price without friction through operational and fulfillment excellence.

The success of AI implementation in this context depends on execution discipline. Retailers making progress are characterized by business leaders, not just technology teams, owning the AI agenda, with priorities set by operations, merchandising, and supply chain. Investing in AI should be anchored in solving operational problems with clear economic weight, building internal foundations, and negotiating external platform deals aggressively.

(Source: Fast Company)