Events & Resources

Learning Center
Read through guides, explore resource hubs, and sample our coverage.
Learn More
Events
Register for an upcoming webinar and track which industry events our analysts attend.
Learn More
Podcasts
Listen to our podcast, Behind the Numbers for the latest news and insights.
Learn More

About

Our Story
Learn more about our mission and how EMARKETER came to be.
Learn More
Our Clients
Key decision-makers share why they find EMARKETER so critical.
Learn More
Our People
Take a look into our corporate culture and view our open roles.
Join the Team
Our Methodology
Rigorous proprietary data vetting strips biases and produces superior insights.
Learn More
Newsroom
See our latest press releases, news articles or download our press kit.
Learn More
Contact Us
Speak to a member of our team to learn more about EMARKETER.
Contact Us

OpenAI’s retail push highlights AI’s data integration hurdle

The news: OpenAI wants ChatGPT to become a default shopping layer, capturing revenues from the majority of its roughly 900 million users who do not pay for its AI subscriptions.

To drive adoption, OpenAI is relying on scale partners. Shopify brings millions of vendors. Stripe brings payments. Together they created the Agentic Commerce Protocol (ACP), but the effort is stalling due to a lack of standards and messy product data, per The Information.

The challenge: Unstructured product data is slowing OpenAI’s commerce push. Without standardized inventory and pricing, AI agents struggle to execute clean transactions. Labels like backorder versus in stock or prices split across systems turn ChatGPT recommendations into errors, raising the risk of failed orders and disputes.

The slowdown is already visible. A Shopify merchant with about $300 million in annual sales applied to OpenAI’s checkout beta. When its CEO followed up with the retailer’s Shopify representative they said the rollout was progressing slowly, per The Information. Here are some reasons why:

  • Inventory blind spots: OpenAI’s shopping assistant struggles with product and inventory data accuracy, causing failures when items shown as available are actually unavailable or mispriced, which leads to broken checkouts and poor experiences, per WeBull.
  • Infrastructure gaps: A merchant’s catalog lives across ERP, pricing, and fulfillment systems, requiring Stripe to act as a translator between AI requests and back-end records that were never designed to talk to agents.

You've read 0 of 2 free articles this month.

Get more articles - create your free account today!