PXM Field Guide · Published 2026-09-16 · Practitioner review pending · Editorial owner: Luke Thompson
Name the task
Vendors group unrelated features under an AI heading: attribute extraction from supplier PDFs, description generation, translation, image tagging, natural-language asset search, duplicate detection, background removal, and portal copywriting. Each is a different task with a different failure mode. Pick the two or three tasks that address a cost you can measure today and evaluate only those.
Confirm availability before you score anything
For each task, record whether the vendor documents it as generally available, in beta, on the roadmap, or unconfirmed, and in which edition, module, and region. Ask for usage limits and any per-use pricing. A roadmap item stays outside the acceptance score until the vendor demonstrates it in the environment you will buy. The Salsify and Bynder release notes on our updates page show how availability and scope differ within one announcement.
Bring your own inputs and a fixed answer key
Prepare a sample with known correct outputs: twenty supplier documents with the attribute values you expect, fifty images with the tags a person would apply, ten product descriptions with the terminology and claims your legal team allows. Use permitted data. Give every vendor the same inputs and do not let them prepare the sample.
Count corrections
For each output, record: correct, wrong, missing, or a claim the source did not support. Time how long an operator takes to review and correct a batch. Compare that time with the current manual process. A feature that produces plausible text quickly but needs a full read to catch invented specifications may cost more than it saves.
Run it twice and check the boundaries
Repeat the same inputs on a different day and compare the outputs. Note variability. Then test the boundaries that matter to you: a protected term that must not be rewritten, a restricted asset that must not appear in a natural-language search result, a regulatory claim that must come from an approved source. Record any output that crossed a boundary as a failed must-have.
Ask where the data goes
Confirm which model provider processes your inputs, whether your data trains a shared model, how long inputs are retained, and where processing happens. Ask for the answer in writing from the vendor, not from a sales call. Your procurement and legal reviewers will ask the same questions.
Decide with a separate line
Keep AI results on their own line in the scorecard with a weight your team agreed on before testing. Our shortlist tool starts AI at 10 percent of the total and lets you change it. A strong AI result cannot rescue a platform that fails a must-have on data modeling, permissions, or integration. A weak AI result is a reason to ask about the roadmap and the price. Keep a platform that runs your core work well.
Sources and scope
Official sources checked 2026-09-15. Vendor statements establish documented scope, not completed testing. The evaluation tasks are PXM Field Guide’s proposed approach.