How Do You Measure Whether Someone Is Actually Good at Working With AI?

Here's a question that sounds simple and isn't: is your team actually good at working with AI, or are they just using it? Using means generating output. Good at working with means the human added judgment, caught errors, maintained context, and produced something the organization can defend. The difference matters because when something goes wrong, accountability doesn't attach to the AI. It attaches to the person who signed off. Every organization deploying AI needs to answer this question. And almost none of them can, because the tools they're using to measure AI skills don't measure collaboration. They measure knowledge. The quiz problem The dominant approach to measuring AI capability in organizations is some form of quiz: multiple choice, scenario-based questions, self-assessment surveys. These tell you whether someone knows what good collaboration looks like. They don't tell you whether someone does it. This is the same gap that exists between knowing you should write tests and a