You’re speeding up something that was already not a bottleneck.
Companies are racing to automate work with AI. But making one task faster doesn't necessarily make the entire organization more productive.
Yue Zhao (Product Leader & Executive Coach) explains that some companies are using AI to accelerate parts of the product development process that weren't actually slowing them down.
You might make research, data analysis, coding, or another task dramatically faster.
But if that task wasn't the real bottleneck, overall throughput may barely change.
The work simply reaches the actual bottleneck faster.
That's why the most important AI automation question isn't just “What can we automate?”
It's “Where is the bottleneck?”
Maybe research isn't the problem. Maybe data isn't the problem. The real bottleneck could be design or another part of the workflow.
AI productivity isn't about making everything as fast as possible. It's about identifying what's actually slowing the organization down and using AI where it can make a meaningful difference.
Are companies automating what's possible instead of fixing what actually slows them down?
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