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Six tech workers share how AI tools are saving them hours weekly — and the challenges that come with it

By

Jacob Zinkula

10d ago· 9 min readenInsight

Summary

Business Insider interviewed six tech workers across various roles to understand how they're using AI tools like ChatGPT, Copilot, and Claude to save significant time on specific tasks. The article explores real-world productivity gains — from a product manager saving 10-15 hours weekly on documentation and meeting prep, to a software engineer cutting code review time by 40%, to a data scientist automating data cleaning. However, it also examines the nuance: the time saved doesn't always translate to reduced workloads, and workers face challenges around accuracy, oversight, and the changing nature of their jobs.

Source

bskySix tech workers share how AI tools are saving them hours weekly — and the challenges that come with itbusinessinsider.com

Key quotes

· 6 pulled
I used to spend about 15 hours a week just on documentation and meeting notes. Now it's down to maybe 3 or 4 hours. That's a full day and a half I get back.
The time savings are real, but it's not like I'm working less. I'm just able to take on more work or focus on the parts of my job that actually require human judgment.
You still have to review everything AI produces. It's not a set-it-and-forget-it solution. If you treat it that way, you'll make mistakes.
The biggest shift is that my job is less about writing code and more about reviewing and debugging AI-generated code. It's a different skill set entirely.
I was skeptical at first, but after using Copilot for a few weeks, I realized I was getting through code reviews in half the time. It's not perfect, but it's a massive productivity boost.
There's this unspoken pressure now to use AI tools. If you're not using them, you're seen as inefficient. But the tools aren't always reliable, and that creates its own stress.
Snippet from the RSS feed
Business Insider asked six tech workers which task AI is saving them the most time on. The gains aren't always reducing workloads.

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