AI doesn't fix bad basic data. It just makes it more visible faster.
New voices are emerging in the PIM industry that believe the next step is that no human will ever need to log in and view their product data. The idea is for AI agents to navigate, update, and distribute the data without a human needing to look at it along the way.
We understand why that sounds tempting. But we think it's one of the riskiest assumptions a business can make with its product data right now.
AI is not a solution — it is an amplifier
Anyone who has worked with product data for many years knows this: bad master data doesn’t get better when more systems access it faster. It gets worse, faster, and in more places at the same time. A wrong unit, a missing EAN code, an outdated price list — today it ends up as a single annoyance in a single channel. Give an AI agent free rein to act autonomously on the same data, and the same error ends up in search engines, marketplaces, customer chats, and partner integrations before anyone has time to discover it.
It's not the agent that's wrong. It's the assumption that you can skip quality control because the tool is new and smart.
Our experience and that of our customers are the same
Through our work with feed PIM, we see the same pattern with customer after customer: AI is a fantastic tool for analyzing product data — finding gaps, detecting inconsistencies across channels, and prioritizing what actually needs to be fixed first. What AI doesn’t do is decide that incomplete or incorrect data is suddenly good enough to be sent out autonomously.
That's why we've built feed PIM around a different idea than "no login required": AI should do the job of analyzing and weeding out noise faster and better than any manual process can — but the decision that data is ready for your twenty channels should still be made by someone who knows your products and your customers.
The complexity is usually greater than one screenshot
Many of our customers use feed PIM for far more than one online store. This often includes B2B and B2C online stores at the same time, industry databases such as NOBB, EFO, RSK, FINFO, etc., document generation for data sheets and product sheets, and printed catalogs that are to be printed physically. Imagine the consequence of an AI agent updating or generating data autonomously, and the error ending up in all these channels at the same time. An error in an online store can be corrected in minutes. An error in an industry database can lie around and affect purchasing at retailers for weeks before anyone catches it. And an error in a print run of several thousand printed catalogs that have already been sent to the printer simply cannot be corrected at all.
The more and more different channels your product data will be released into, the more expensive it becomes to automate away the last checkpoint.
Login isn't friction. It's the checkpoint.
Removing logins from a PIM is not the same as removing complexity. It is removing the last place in the chain where a human could stop an error before it went global. For businesses with hundreds or thousands of products, distributed across multiple marketplaces, online stores, and dealer networks, it’s not a detail — it’s the risk picture itself.
We don't believe the future of product data is "no humans involved." We believe it is: AI does the analysis, humans make the decisions, and the system is built to make that division of labor as fast and easy as possible.
