---
id: "action-structure-machine-readable-data"
type: "action-item"
source_timestamps: ["§ What Comes Next: Competing for an AI Customer's Preference"]
tags: ["tactical", "data-infrastructure"]
related: ["concept-ai-engine-optimization", "framework-agentic-tech-stack"]
speakers: ["Kartik Hosanagar"]
action: "Open machine-accessible back doors and structure product data for AI agent querying."
outcome: "Enables AI agents to discover, evaluate, and potentially purchase your products autonomously."
sources: ["geo"]
sourceVaultSlug: "hbr-seg-geo"
originDay: 3
articleStem: "hbr-tier2-05-market-to-ai-customer"
sourceUrl: "https://hbr.org/2026/06/how-do-you-market-to-an-ai-customer"
sourceTitle: "How Do You Market to an AI Customer?"
---
# Structure product data for machine readability

**Action:** Open machine-accessible back doors and structure all product catalogs, pricing, and inventory data so AI agents can query and transact.

**Why:** This is the baseline requirement — the **Commerce Layer** of the [[framework-agentic-tech-stack]] — for participating in [[concept-agentic-commerce-d5]]. Structuring feeds and schema is also the substance of [[concept-ai-engine-optimization|AEO]]. But note the caveat: AEO solves for **visibility**, not persuasion (see [[contrarian-visibility-vs-persuasion]]); machine-readability is necessary but not sufficient.

**Outcome:** Enables AI agents across ecosystems (via [[concept-commerce-protocols|ACP/UCP]]) to discover, evaluate, and potentially purchase your products autonomously.

*Enrichment note:* practitioner guidance consistently emphasizes structured product feeds, schema markup, and protocol compliance as the entry ticket to appearing inside AI responses and commerce cards — while distinguishing visibility metrics from actual conversion.


## Related across articles
- [[action-structure-content-machines]]
- [[action-prepare-ai-customers]]
- [[action-build-machine-readable-trust]]