How tech workers are leveraging AI to save time each week

Ask any technology employee how AI has changed their job, and you’re likely to hear something like this: single Number: Time saved.

In interviews with Business Insider, software engineers, product managers, and data scientists at Big Tech explained how they use AI to compress hours of work into minutes. They use it to draft documents, summarize months of meetings, review code, automate reports, and more.

However, faster doesn’t necessarily mean easier. One Amazon data scientist said AI is increasing his work week by building automated systems that should ultimately save him time. Another Amazon employee said the time saved is quickly redirected to the next project.

Here’s how six tech workers say AI saves them the most time. (Their answers have been edited for length and clarity.)

Time saved by AI is reinvested into the next problem

Priyanka Devi Ramesh is a Business Intelligence Engineer at Amazon. She is 30 years old and lives in Virginia.

The area where AI has had the biggest impact is document creation. With the help of an AI tool called Pippin, it’s now easy to translate your thoughts about the projects you’re working on into polished documentation for technical and customer use. This saves a lot of time. It now takes only 15 to 20 minutes at most to create and complete documents that previously took over an hour.

On the technical side, we use Kiro and Amazon Quick. Kiro is great for brainstorming ideas and updating logic in minutes. I’m building an agent within Amazon Quick to automate common customer questions on dashboards and uncover insights from data.

AI hasn’t reduced my working hours. We’re always looking for ways to clean up messy data and finding opportunities to automate wherever possible. So time saved in one area is reinvested in the next problem.

AI helps make sense of months of meetings at Google

Prerit Pathak is a security engineer at Google. He is 27 years old and lives in New York City.

I use Gemini for a variety of purposes, most recently for note-taking.

I would take shorthand notes during meetings to record interesting or important information. I now use Gemini to take notes on my work calls, and the improvements have been amazing. Summary tasks that once took 1-2 hours, such as understanding what happened in the past 6 months, now take 5-10 minutes.

I’m working long hours now, so AI will save me time later.

Sarthak Gupta is a data scientist at Amazon. He is 29 years old and lives in Seattle.

AI is most useful for building end-to-end automation pipelines for repetitive workflows.

Previously, it took 8-10 hours over several days to create a monthly stakeholder report, which included retrieving data, cleaning it, generating visualizations, creating summaries, and more. Currently, an AI pipeline handles pulling data, transforming, and updating dashboards. Take about 45 minutes to review the output and add context before submitting.

However, overall working hours are currently longer than usual. The reason is that we are in the middle of an automation phase. Building pipelines, integrating AI tools, validating outputs, and onboarding all of these into existing workflows is front-loading work, and the upfront investment is real. The reward comes later when the same task that took days is completed with the click of a button.

So, in the short term, the AI ​​is actually adding hours to my week instead of subtracting them. We expect this situation to reverse as basic pipelines stabilize and automation does the heavy lifting automatically.

AI helps turn messy ideas into sophisticated plans

Tanvi Pisal is a UX designer working as a contractor for Apple via Red Oak Technologies. She is 29 years old and lives in San Jose.

One of the biggest ways AI can save time is in early-stage product thinking and documentation.

As a product designer, I would spend hours drafting product requirements documents, brainstorming user stories, mapping edge cases, outlining usage scenarios, and refining ideas before embarking on visual design.

Now you can start with a rough note or a messy draft, and AI will help transform it into a more structured document in minutes. What used to take 3-4 hours can often be reduced to 30 minutes with feedback and refinement.

Amazon helps you get to the starting line faster thanks to AI

Udit Mehrotra is head of product at Amazon. He is in his 30s and lives in Seattle.

The biggest change I’ve noticed is in the creation of product documentation. Every major Amazon initiative starts with documentation, and for years, the first hour or two of that process was getting the footing. That meant setting up a structure, filling in sections you knew by heart, and building something worth reacting to before you got into actual thinking.

Now, using AI, you can input your customer’s problems and constraints and produce a solid first draft in minutes. What surprised me was that many of them were more comprehensive than what I had written myself given the time constraints.

Getting from 80% to 100% is still the realm of real work, and AI won’t change that. The thinking still requires the same depth and care as it always did: strategic judgment, trade-offs between what the customer needs and what is technically feasible, and decisions that require years of accumulated context about specific customer problems.

What has changed is that we get to the starting line faster and have a more complete structure to react and push. As a result, the quality of the final document is often improved. This is not because the AI ​​thought hard, but because I spent a lot of time on it.

What used to take a week now takes one day

Iren Azra Zou is a software engineer at trucking logistics startup Double Nickel. She is in her 20s and lives in New Jersey.

I use AI for most of my coding (mainly Claude Code). Honestly, it’s hard to quantify the time savings. What used to take me a week now feels like a day.

We also rely heavily on AI for code reviews and feedback unless it’s a particularly risky change. That alone will save you a ton of time. Instead of waiting days for a human review, you can get multiple rounds of feedback within hours. You’ll also spend less time reviewing other people’s code, potentially saving yourself several hours each week.

There are trade-offs. Fewer human reviews can have downsides. But right now, speed of iteration and innovation is incredibly valuable to us.

Do you have a story to share about how you’re navigating a crossroads in your career? If so, please contact our reporter via email. jzikula@businessinsider.comor via Signal at jzikula.29.