Study finds people systematically overestimate AI efficiency gains on basic tasks, expecting 55.7 seconds of savings but getting 7.5
Repeated use triggers a feedback loop of over-reliance.
Repeated use triggers a feedback loop of over-reliance.
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This is why I keep saying there’s a huge gap between textbook AI studies and actual real-world practice. Out here, AI is an execution tool. It stops projects from stalling out in endless meetings so people can execute, clear their plates, and immediately free up mental bandwidth for the next revenue driver. 🔑 This goes beyond speed; it's about real-time risk mitigation. During a live project call, an individual I coached to leverage AI's full breadth used it to instantly catch a critical SQL error. If that code had been pushed to prod, it would have caused a massive revenue loss. Instead of scheduling three follow-up meetings and submitting a dev ticket, they caught the bug on the spot and protected the bottom line. If experts think AI slows teams down or makes them lazy, they just aren't curious enough to learn how to use it properly. Real-world expertise is about knowing how to leverage the technology as the ultimate sounding board for strategic thinking and execution. That’s what we’re teaching and will continue to teach. It takes work but is doable!
