One of the learners I remember best earned credit for a life spent on the land. Trapping, harvesting, the kind of knowledge a written test would never see. Another was a parent whose years of raising children finally got read as learning rather than as time away from it. In prior-learning assessment you do not hand people a test that pretends they know nothing. You ask them to document what they can already do, and you assess the evidence and the judgment behind it.
That is the whole model, and it was AI-proof before AI existed. Recognition of prior learning never assessed a product a machine could fake. It assessed documented process, real artifacts, and the reasoning that ties them to a standard.
Evidence, not gaps
The move that makes it work is a stance. You read a life as evidence rather than as a deficit. A portfolio is an argument the learner builds: here is what I did, here is what it demonstrates, here is how it maps to the outcome. Turning experience into a defended claim is exactly the cognitive work AI cannot do on the learner’s behalf (Kolb, 1984).
Prior-learning assessment survived AI before anyone needed the phrase. It assesses documented process and judgment, not a product.
What every assessor can borrow
You do not need a formal recognition mandate to use the logic. Ask for the portfolio, not just the product. Ask the learner to show the decisions, name the standard their evidence meets, and defend the fit. I have watched the moment a learner realises their own experience counts, and it changes how they show up for everything afterward. The design is honest, it is humane, and it holds up against shortcuts.
Why AI raises the stakes
As product-based assessment loses its meaning under AI, the practices that already assess process stop looking like exceptions and start looking like the model. The returning adult with a portfolio is not an edge case to accommodate. That learner is the template for assessment that still means something.
The move
Add one portfolio element to a course that has none. A short, evidenced claim the learner has to defend. It is the smallest step toward assessment that AI cannot hollow out.