Don't Surrender Standards: Who Decides Whether AI Work Is Any Good?

Marcus Torres is the Chief Product Officer at Quickbase.

​One of the most overlooked aspects of AI’s impact on organizations is how it will affect standards of excellence. While there’s a lot of talk right now about how AI might replace skills or create efficiencies, the real danger for companies of all sizes is mistaking the approval of AI work for judgment of quality.

AI does more than just change who does what work. It changes who develops the judgment to know whether that work is good. ​

The Shift From Creating To Approving

Here’s the pattern to look for: As AI takes on more work doing the building—whether that’s code, copy, analysis or the first draft of nearly everything—more people are quietly sliding from the role of creator to approver.

This can often feel like progress, freeing team members from menial tasks. But it’s a double-edged sword if you’re not careful—because those menial tasks mean something. They can create or deepen human judgment, which stops people from becoming irrelevant. Or, at the very least, those tasks are what allow people to build a sense of what’s good and what’s not. ​

In other words, many organizations are still asking, “Can AI do this work?” Yes, of course it can, and it can do that work increasingly well. But there’s a more important question that’s not getting asked as frequently: Who decides if the work is any good?

Defining What ‘Good’ Looks Like​​

You might say that there are people who check the work that AI does, and they’re the ones who decide if it’s good. That’s true, but only to a point. Developer surveys are already showing just how far that goes. The reality is that trust in what AI has generated, like code accuracy, has fallen, even as AI usage has steadily climbed. People are approving AI, even as they either believe it less or, worse, question it less. That’s not oversight. ​