Beyond the Storefront: How ACP Expands the Role of the Merchandiser

From Storefront to Everywhere

For decades, merchandising has centered around a simple question: How does a visitor find the right product once they land on a merchant’s website?

Product listings, search results, category pages, and personalized recommendations have been the levers merchandisers pull to connect shoppers with products and drive conversions.

But the digital commerce landscape is shifting again—this time, beyond the merchant’s site. With the introduction of the Agentic Commerce Protocol (ACP) by OpenAI and Stripe, AI agents are becoming a new interface between consumers and merchants. ACP allows shoppers to interact with AI assistants that can research, compare, and even complete transactions across multiple merchants—securely, transparently, and with the merchant still fulfilling the order.

This shift redefines product discovery. The question for merchandisers is no longer “How do I optimize my category page?” but “How does my product get discovered when the shopper never even visits my site?”

ACP and the New Era of Product Discovery

The Agentic Commerce Protocol establishes a standardized way for AI agents to communicate with merchant systems—passing order details, handling payment, and maintaining data security. For shoppers, this means they can say, “Find me a new pair of trail running shoes under $120,” and the agent handles everything from search to checkout.

For merchandisers, however, this marks a profound change. Discovery is now decentralized. Instead of customers navigating a carefully designed site experience, AI agents become the primary interface for browsing, comparing, and purchasing.

That means the context of merchandising expands:

• Product information must be structured, consistent, and machine-readable.
• Content, pricing, and availability need to be instantly accessible via APIs and data feeds.
• Merchandising strategy must anticipate how AI agents interpret and rank products across a much wider digital ecosystem.

Merchandising shifts from managing onsite experiences to ensuring omnipresent relevance.

The Merchandiser’s Role: From Curator to Orchestrator

Historically, merchandisers have been curators—arranging digital shelves, tuning search relevance, and shaping the visual presentation of a brand’s catalog.

In an ACP-enabled world, the merchandiser becomes something broader: an orchestrator of data, signals, and AI context.

Here’s how that evolution plays out:

Instead of just showing products well, merchandisers must now ensure their data tells the right story to AI systems—through metadata, descriptions, and relevance cues that influence how agents represent and recommend items.

Why Effective Merchandising Tools Matter More Than Ever

In this new model, the quality of a brand’s merchandising technology stack determines its visibility in agent-driven commerce.

ACP doesn’t eliminate the need for strong merchandising—it amplifies it.

To be successful, merchandisers will need:

• Unified Data Management: Product data, inventory, and pricing are structured in ways AI agents can consume instantly.
• Semantic and Attribute-Level Control: Tools that expose the intent behind products—what they are, who they’re for, and why they matter.
• Analytics That Span Channels: Insight not just into what’s happening onsite, but how products are being surfaced and purchased via agents.
• Automation With Oversight: AI-driven merchandising that adjusts in real time, but with clear human control over strategy, compliance, and brand voice.

As ACP adoption grows, these types of intelligent, flexible merchandising platforms will become the connective tissue between merchants and AI ecosystems.

The Merchant’s New Frontier: Visibility Without Presence

ACP doesn’t replace eCommerce websites—it extends them. But in doing so, it changes the rules for visibility.

A shopper may never visit your homepage. They might engage entirely through a digital agent that:

• Pulls your product data through ACP,
• Compares it with competitors, and
• Recommends the best fit.

To remain competitive, merchandisers must ask:

• How will agents interpret my product catalog?
• Do I provide the right contextual data (attributes, images, reviews, relevance signals)?
• Can my systems respond fast enough to real-time queries and updates?

The merchants who treat ACP as a new discovery channel—not just a checkout mechanism—will lead the next phase of digital commerce.

Preparing for the Agentic Future

To thrive in the ACP era, merchandisers and their organizations should focus on three key strategies:

1. Invest in Data Readiness
   • Standardize attributes, taxonomy, and metadata.
   • Ensure your product data is accurate, rich, and structured for machine interpretation.
2. Embrace AI-Native Merchandising Tools
   • Adopt platforms that let merchandisers collaborate with AI, not compete against it.
   • Enable real-time product optimization, category management, and recommendations that feed both humans and AI agents.
3. Redefine Success Metrics
   • Expand KPIs beyond onsite conversion to include agent-driven visibility, recommendation inclusion rate, and multi-channel performance.

The Expanding Influence of the Merchandiser

The Agentic Commerce Protocol signals a shift toward a more interconnected commerce ecosystem—where discovery, decision, and purchase can happen anywhere, guided by AI.

Far from making merchandisers obsolete, it elevates their importance.

Merchandisers will shape how brands are represented to intelligent systems, not just human shoppers. They’ll ensure AI agents understand their products as accurately and persuasively as customers do. And they’ll depend on the next generation of AI-powered merchandising platforms—to manage that complexity with clarity, control, and creativity.

Key Takeaways

1. ACP decentralizes product discovery, making AI agents a new shopping channel.
2. Merchandisers evolve from site curators to ecosystem orchestrators, guiding how AI systems interpret and promote products.
3. Strong merchandising tools are essential—bridging structured data, AI optimization, and human oversight.
4. The future of commerce belongs to brands whose data, not just their design, is merchandised well.