These costs could be ignored, or even accepted, if there was a clear idea of how precisely AI would streamline and improve the workplace—or offer any tangible public benefit significant enough to make these underlying trade-offs acceptable. But the answers to these questions remain extremely tenuous. According to a February 2026 paper by the National Bureau of Economic Research, 80 percent of companies that have begun actively using AI have reported no impact on company productivity. A separate, widely cited 2025 MIT study revealed that 95 percent of corporate AI pilot programs received zero return.
Even within tech and coding, one of the areas where AI is reported to have the most promise, there’s the question of whether the productivity gains reported can be trusted. In a provocative GitHub post, machine-learning engineer Han-Chung Lee argued that even rosy internal numbers that do show AI-assisted productivity gains are suspect, as they’re produced to hit adoption targets no one can effectively audit.
This isn’t to say that AI doesn’t show immense and possibly incredibly valuable potential, especially bearing in mind that ChatGPT (which can be considered the first mainstream demonstration of AI technology) was only launched in November 2022. It’s natural for new technology to have a bumpy adoption period as both users and designers stress-test its strengths and limitations in the real world.