Agentic Commerce Readiness: Why Mid-Market Brands Should Pay Attention

Agentic commerce is no longer a concept being debated in boardrooms. It is operational infrastructure being built right now by the largest technology and payments companies in the world.

For mid-market brands, the question is not whether this shift will matter. It is how prepared their systems, data, and operations are to participate when it does.

What Agentic Commerce Actually Means

Agentic commerce refers to a model in which AI agents act on behalf of customers to discover products, compare options, and complete transactions. These agents interpret user intent and can execute multi-step purchasing decisions without direct human interaction at every step.

Instead of customers manually browsing websites, an AI system evaluates available products, assesses price and compatibility, and recommends or purchases the best option. The buying journey shifts from human-led browsing to machine-mediated decision making.

Visibility is no longer determined only by search rankings or advertising placement. It increasingly depends on how well machines can interpret and trust a brand's product data.

The Structural Shift Is Already Measurable

Consumer behavior has moved ahead of most brands' infrastructure. According to McKinsey's AI Discovery Survey, half of consumers now intentionally seek out AI-powered search engines, and a majority say it is the top digital source they use to make buying decisions. 

The infrastructure supporting that behavior is scaling fast. On March 24, 2026, OpenAI expanded its Agentic Commerce Protocol to support product discovery inside ChatGPT, with Target, Sephora, Nordstrom, Lowe's, Best Buy, The Home Depot, and Wayfair already integrated.

When half of consumers are starting their purchase journeys with AI and major retailers have already integrated their catalogs into AI-native commerce protocols, the channel is not emerging. It has arrived.

Why Mid-Market Brands Are Most at Risk

Large enterprises have the engineering resources and internal infrastructure to experiment early. Mid-market brands typically operate with smaller technical teams and legacy commerce systems. That gap matters now in a specific way.

When Merkle tested AI agents for product recommendations, all research and pricing happened inside the large language model. Brand websites never loaded. Marketing copy did not include the technical specifications agents needed. Even detailed product descriptions fell short without structured attributes in machine-readable formats.

Most mid-market brands are still running product data designed for human eyes. Marketing copy. Unstructured descriptions. Inconsistent attributes across SKUs. That data was never built for machine interpretation, and AI agents cannot work with what they cannot parse.

The result is a visibility gap that widens every week the infrastructure question goes unanswered.

What Readiness Actually Requires

SAP framed the practical steps clearly at NRF 2026.

Three things are now necessary for any brand serious about agentic commerce: restructuring product data to be machine-readable, adding semantic summaries for LLM reasoning, and tagging products by the problems they solve, not just their attributes. 

These are not advanced technical projects. They are foundational data hygiene decisions that mid-market brands already have the access and tools to begin. Brands with existing GS1 accounts already have a starting point.

The Verified by GS1 standard provides a globally recognised product identity layer that AI systems can read and resolve. What has changed is the urgency of completing it.

The Window Is Now

According to Juniper Research, global spending through agentic commerce is projected to reach $1.5 trillion by 2030, growing from only pilot deployments in 2025 and 2026. 

The brands that capture that opportunity will not be the ones who waited for the channel to mature. They will be the ones who built the data infrastructure while everyone else was still debating whether agents would really shop.

If you are a mid-market brand and you are not sure where your product data stands, that is exactly what our Digital Identity Audit is designed to answer. Let's talk.