Agentic Commerce Readiness Rated Just '3 to 4 Out of 10' -- SAP CX Chief Warns of a Data Foundation Crisis

AI Agents Are Creating "Invisible Retailers"

Agentic commerce demands better data - most retailers aren't prepared

For years, digital commerce strategies were built around simple assumptions: humans search, humans browse, and humans decide. These assumptions no longer hold true.

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For years, digital commerce strategies were built on a simple premise: humans search, humans browse, and humans decide. That premise no longer holds. A commentary by Balaji Balasubramanian, President and Chief Product Officer of SAP CX, published in Chain Store Age, exposes the retail industry's critical data preparedness gap for the agentic commerce era.

In a PYMNTS interview, Balasubramanian stated plainly that on a scale of 1 to 10, most retailers rate only "3 to 4 at best" for agentic commerce readiness. The core issue is not a lack of data, but how that data is organized, harmonized, and accessed.

Bots Have Surpassed Humans -- The Internet's Tipping Point

Backing up this warning, a report published by HUMAN Security in March 2026 confirms that automated bot traffic has overtaken human traffic on the web. AI traffic surged 187% in 2025, with automated traffic growth rates reaching roughly eight times that of human activity.

According to CNBC reporting, over 95% of AI-driven traffic is concentrated in three industries: retail and e-commerce, streaming and media, and travel and hospitality. In other words, retail websites are already receiving more visits from bots than from humans.

Consumer purchasing behavior is also shifting. Instead of typing keywords into search boxes, a growing number of shoppers are asking LLMs directly for advice. These prompts are longer, more specific than traditional search queries, and convert at surprisingly high rates.

Why Most Retailers Are Invisible to AI Agents

The crux of Balasubramanian's argument is that agentic commerce is fundamentally a "data challenge," not a "channel challenge."

AI agents do not shop the way humans do. They are not swayed by marketing copy or infer meaning from design. For an agent to function, it needs to understand precisely what a product is, who it is for, whether it is available, and why it is relevant. Yet most retail sites were never designed for this kind of machine-level interpretation.

Mirakl's research found that leading tech partners rated retailer AI commerce readiness at an average of 4.4 out of 10. While 76% of retail leaders acknowledge the need to reinvent their business models around AI, 67% still struggle to collect and operationalize their own product and customer data.

Product data is often fragmented across multiple systems, with incomplete or inconsistent attributes. Inventory and fulfillment information suffers from delays and silos. Since AI agents will not recommend products they cannot confidently understand, those products effectively vanish from the agent-driven funnel.

Three Priorities for Agent-Ready Retail

Balasubramanian outlines three priorities for retailers preparing for the agent era.

1. Make product data explicit and machine-readable

Move beyond basic descriptions to include clear attributes such as size, dimensions, compatibility, materials, and variants. If an AI agent cannot confidently compare options, it simply will not recommend them.

2. Provide meaningful semantic summaries

Structured data alone is not enough. Semantic summaries that explain who a product is for, what problem it solves, and why it is relevant enable more accurate agent recommendations. Two products may share similar specs but serve entirely different audiences -- semantic context is what helps agents make that distinction.

3. Organize products by the problems they solve, not just categories

As discovery becomes intent-driven, consumers describe the outcomes they want rather than searching for specific brand names or product types. Problem-based tagging increases the chances of being surfaced by AI agents, even in prompts where brand names are never mentioned.

What E-Commerce Businesses Should Do Now

Balasubramanian is unequivocal: "Data foundation is how you can win in the agent era." This view extends beyond SAP. Microsoft noted in a February 2026 blog post that agentic commerce is becoming "the new front door to retail."

A critical point is that it is inherently impossible to advertise to AI agents. Traditional digital marketing tactics simply do not apply. The winners will be brands that build data foundations enabling agents to act with certainty on behalf of consumers.

The window for action is narrowing fast. With bot traffic surpassing humans and AI agent-driven product discovery becoming the norm, data readiness is no longer optional -- it is the price of participation. Start by auditing your product data for machine readability, then prioritize adding semantic summaries and implementing intent-based product classification.