"While AI is delivering productivity gains, those gains are being partially washed away when technologists or employees need to go back to implementations to fix mistakes, rewrite content, or double-check outputs. At least 37% of time savings gained through AI are lost to fixing low-quality output, according to the survey's authors, which included the experiences of 3,200 practitioners. It's the ultimate AI productivity paradox, the Workday authors argue."
"'Don't build an agent when a basic chat will do,' development guru Corey Noles explained in a recent webcast. All too often, people will spend an inordinate amount of time attempting to build a complex AI system when a simple prompt may do the trick. It takes some level of expertise and training to understand the difference and the best approaches."
"The speed gained through AI's time savings "doesn't always translate into better outcomes." At least 85% of employees report saving one to seven hours per week using AI. However, the follow-up rework required washes out the savings -- to the tune of an average 1.5 weeks a year spent fixing AI outputs, the survey analysts estimate."
AI delivers measurable time savings for many employees, with at least 85% reporting one to seven hours saved per week. A substantial portion of those savings is erased by follow-up rework: an estimated average of 1.5 weeks per year spent fixing AI outputs. About 37% of time saved is lost to addressing low-quality output. Only a small share of employees consistently achieve net-positive outcomes. Many workers lack sufficient AI training, and overengineering AI solutions often wastes time compared with simpler approaches. More investment in training, people, and job redesign is needed.
Read at ZDNET
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