The people who label and evaluate your data are workers, and how they are classified is a real legal question. Get it wrong and you inherit liability, back-pay exposure and reputational risk.
Why it is hard
Classification rules differ by country, and AI data work is new enough that many platforms simply ignore the question. That is a risk you do not want sitting inside your supply chain.
What misclassification actually risks
Getting classification wrong is not a paperwork error. Depending on the jurisdiction it can mean back-payment of taxes and social contributions, penalties, and reclassification of contractors as employees with the entitlements that follow. It can also surface in customer due diligence and damage trust in your supply chain.
Getting it right
Work with a partner that engages experts with jurisdiction-correct classification, transparent terms and reliable payment. Clean classification is not just compliance, it is how you attract better contributors: professionals are far more willing to do serious work for a platform that treats them correctly.
Why this is hard to do in-house at scale
Classifying a handful of contractors in one country is manageable. Doing it correctly across many EU jurisdictions, each with its own tests and thresholds, and keeping it current as rules change, is a specialised, ongoing job. This is one of the strongest reasons teams use a platform rather than build.
Outsource the hard part
Pathwize handles clean, jurisdiction-correct classification across the EU so you do not have to. Book a demo to learn more.