Even prolific shoppers have a hard time with complex purchases. Take home appliances, for example. Until recently, finding a washing machine was overwhelming. It required hours of cross-referencing technical specs, customer perspectives and expert reviews. Effectively, you had to become an expert just to buy one that fit your needs.

With agentic commerce, LLM-powered agents synthesize that information instantly. A tedious process is boiled down to a simple prompt: I need a washing machine for a small bathroom that handles five people, including three kids who love to play in the mud.

Shoppers are moving from searching for products with keywords to having conversations with AI agents, providing them with more context than possible before. And we're not just seeing this on a small scale. Gartner reports 60% of shoppers already use AI, and McKinsey research reveals that by 2030, the US retail market could represent revenue in the range of $900 billion to $1 trillion orchestrated by agents.

This represents a massive shift in how we shop and how eCommerce is conducted today. In this new reality, your shoppers are just as likely to be AI agents as they are humans. Raising the critical question: how can retailers ensure AI agents choose their offers over the competition? 

How retailers can prepare for agentic commerce today

Across the shopping journey—discovery, evaluation and purchase—LLMs are increasingly dominating the first two phases, even if they aren't autonomously buying yet. For retailers, the urgency is real: AI agents are already shaping which brands and products make it to consideration. Fortunately, there's a clear path forward—three steps that will ensure retailers remain competitive.

Step 1: Build out assortment to fill product gaps

AI agents are designed to complete tasks as efficiently as possible, including building optimal multi-item baskets. If your assortment has gaps, the agent won't wait around: it will complete the basket using multiple storefronts.

Retailers who offer a wide, relevant assortment from a single, centralized data source give agents a powerful reason to stay. By expanding assortment through marketplace and dropship strategies, you dramatically increase the chances an agent will build an entire basket with you—rather than piecing it together across competitors.

Step 2: Optimize product detail pages for LLMs

In the age of LLMs, your product data is your digital salesperson—and it needs to be comprehensive, structured and AI-readable. Low-quality or incomplete data makes products invisible, as AI agents prioritize rich, detailed content when ranking results.

Building an AI-ready foundation requires two key elements:

First, enforce rigorous data quality standards. Ensure mandatory fields are complete and attributes follow structured formats that LLMs can parse efficiently.

Second, embrace depth. Provide high-resolution images, detailed descriptions and complete technical specifications. AI agents need this information to accurately match complex user prompts to your products—sparse data means you won't make the shortlist.

Step 3: Prioritize operational reliability

AI agents don't just seek relevance, they demand reliability. A perfect product recommendation means nothing if fulfillment is uncertain.

To win with AI agents, retailers must excel in three operational areas:

First, maintain real-time inventory accuracy. Agents quickly discard out-of-stock items, so synchronized inventory data is non-negotiable.

Second, guarantee fulfillment performance. LLMs assess historical data and favor retailers with proven track records and strong service level agreements.

Third, ensure seamless post-purchase experiences. Easy returns and responsive support signal the operational excellence that builds agent trust.

When you excel at operational reliability, AI agents don't just recommend your products, they’re more likely to complete the entire transaction through your storefront.

The critical role of marketplace tech in agentic commerce

Executing the steps above requires the right infrastructure. Marketplace technology is uniquely designed to deliver on all three requirements—providing the operational foundation that makes assortment expansion, data excellence and reliability achievable at scale:

• Greater assortment: Marketplaces easily fill product gaps, increasing competitiveness, discoverability and match rate.
• Product data excellence: Marketplaces require structured data, which is crucial in the age of AI. Better, structured product data means higher rankings and a greater chance an LLM will recommend your products.
• Operational reliability: LLMs prioritize reliability. Marketplaces help maintain delivery promises, synchronize inventory, provide seamless fulfillment and ensure consistent customer experiences.

Marketplace architecture serves as the optimal operational backbone for the agentic age, automating complex assortment and data management so retailers can focus on strategic growth.

Securing your future in the AI era

Agentic commerce is here. Retailers who master assortment breadth, pristine product data and operational reliability will thrive in this new landscape. Those who don't risk becoming invisible.

The opportunity is clear: transform your storefront into an AI-optimized destination that wins at discovery, evaluation and purchase. The retailers who act now will define the next era of commerce. Will you be one of them?