---
id: "prereq-pim-systems"
type: "prereq"
source_timestamps: ["\\\"§ 1. Structure your content for machines", "not just humans.\\\""]
tags: ["infrastructure", "data-management"]
related: ["concept-generative-engine-optimization"]
reason: "Required to implement Generative Engine Optimization (GEO) and make product data accessible to AI agents."
source_url: "https://hbr.org/2026/02/how-brands-can-adapt-when-ai-agents-do-the-shopping"
source_title: "How Brands Can Adapt When AI Agents Do the Shopping"
sources: ["geo"]
sourceVaultSlug: "hbr-seg-geo"
originDay: 3
articleStem: "hbr-ext-14-brands-adapt-ai-shopping"
sourceUrl: "https://hbr.org/2026/02/how-brands-can-adapt-when-ai-agents-do-the-shopping"
sourceTitle: "How Brands Can Adapt When AI Agents Do the Shopping"
---
# Product Information Management (PIM) Systems

**Prerequisite.** The source assumes the reader understands what a **PIM (Product Information Management) system** is and how e-commerce platforms use **APIs and web markup standards** to distribute product catalogs.

**Why it's required:** to implement [[concept-generative-engine-optimization-d14]] and make structured product data accessible to AI agents (see [[action-structure-content-machines]]).

> **Enrichment / canonical references.** Foundational data standards and PIM tooling that embody the practice: **GS1** (global trade item numbers and attribute schemas, https://www.gs1.org), **schema.org Product markup**, product-feed standards, and major PIM vendors such as **Salsify** and **Akeneo**. These are the concrete building blocks brands use to expose machine-readable catalogs.


## Related across articles
- [[prereq-structured-data]]
- [[prereq-llm-parsing]]