Duolingo's employees had one question for their CEO. Do you just want us using AI for AI's sake?
In late 2024 and early 2025, Luis von Ahn pushed a plan across the language learning company that tied employees' AI usage to their performance reviews. In an internal memo, he said Duolingo would move with urgency on adoption and accept occasional small hits on quality. The goal, according to reporting on the memo, was to get everyone, not just engineers, using AI tools in their daily work.
What actually happened is what tends to happen when you measure the tool instead of the work. Employees started cramming AI into workflows where it added friction, created extra review cycles, and produced worse output. Not because it helped but because it showed up on a scorecard.
"It felt like, rather than being held accountable for the actual outcome, we were trying to just push something that in some cases did not fit," von Ahn said on the Silicon Valley Girl podcast in April 2026.
So he pulled the whole thing back. The only metric that matters now is whether you're doing your job well. AI helps a lot of the time, and when it does, use it. By May, von Ahn was telling Stanford's Graduate School of Business that human designers at Duolingo still outperform AI on creativity and polish, and that the company would not lower its quality bar to hit an adoption target. A Duolingo spokesperson offered the predictable company line that AI tools assist with that work and don't make decisions or replace the people building Duolingo. Von Ahn's unscripted interviews told a much more interesting story.
Duolingo's AI content pipeline continued to produce large volumes of material, even as the internal AI-usage mandate was backfiring. AI did great work when it was matched to a specific problem that needed solving. It collapsed the moment adoption became the point.
Von Ahn isn't the only CEO recalibrating. Mark Zuckerberg reportedly acknowledged that Meta made mistakes during its own AI workforce restructuring, and until recently, Meta was running a leaderboard of its top AI token users so employees could see how much AI their colleagues were burning through. As Gizmodo has reported, CEOs are quietly stepping back from the aggressive rhetoric that dominated 2025. But most of those reversals are about headcount and layoffs. Von Ahn's finding is more specific and more useful. You can have AI tools that genuinely work and still destroy their value by making adoption a performance metric.
According to a 2025 Writer report, 31% of employees across industries were actively resisting their company's AI rollouts. Some were reportedly tampering with metrics to make AI look like it was underperforming. Others were doing the work by hand and then reverse-engineering an AI trail so management would see the right numbers. Von Ahn acknowledged that many other tech companies are doing similar things behind the scenes. He's probably right. He's just the one who said out loud that it didn't work.
Von Ahn ran the AI mandate experiment that every other CEO is considering and then did something almost nobody does. He published the results. AI adoption works when it solves a problem people already have. It collapses when it becomes the metric itself. If your company is building an AI usage scorecard right now, or tying adoption to promotions, or tracking token counts on a leaderboard, Duolingo just showed you how that movie ends. Measure the work and let the tool follow.
