When a new technology shows up, most people ask, “Whose job will this replace?”
A better question is, “What new work will this create?”

In a recent interview with Every, Box CEO Aaron Levie shared a useful way to think about AI. He said AI agents don’t shrink human work. They expand it. By taking care of repetitive coordination, AI gives teams more room for creative thinking and faster experimentation.

This idea matters for any product team exploring AI. It’s not about copying what Box did. It’s about learning how automation can grow the total surface area of what your team can do.

From automation to amplification

Most companies start with AI because they want to save time or reduce costs. That’s fine as a starting point, but it’s not where the real value lies.

Once those efficiencies add up, they free capacity. And capacity is what you use to explore, test, and build.

When teams use that time to push new ideas forward, automation turns into amplification. It multiplies what people can accomplish instead of just making the same work faster.

The Expansion Loop

You can think of AI-driven growth as a simple loop:

  1. Automate: Find and offload repetitive or coordination-heavy work that consumes energy but adds little insight.
  2. Reallocate: Redirect that saved time toward higher-value work like customer research or quick experiments.
  3. Experiment: Run more small tests and shorten feedback cycles.
  4. Expand: Use what you learn to open new directions or build features that were once too time-consuming to explore.

Then repeat. Each loop feeds the next.

What this looks like in practice

A GitHub study showed how developers using Copilot worked faster but also reported 55% higher satisfaction. The reason wasn’t just speed. It was because they spent more time solving creative problems and less time typing boilerplate code.

AI didn’t replace developers. It changed what productivity meant. Routine work moved to the background, and creative work came to the front. The total output increased because the focus shifted.

Finding your own expansion opportunities

Here are a few ways teams can put this into practice:

  • Spot friction, not just repetition. Look for coordination pain points. These are often better targets for AI than pure task automation.
  • Plan for reinvestment. Don’t let saved time disappear into the calendar. Decide where it goes before you start.
  • Update what you measure. Instead of counting tasks, count experiments, insights, and customer improvements.

Designing for growth

How leaders frame AI matters. If teams think automation means fewer jobs, they’ll avoid using it. The companies that benefit most are clear that AI expands capacity and impact.

For product and engineering leads, that means saying out loud: AI won’t replace judgment or creativity. It gives you more room to use them.

The next curve

The last digital transformation digitized manual work. The next one scales cognitive work. The advantage will go to teams that use automation gains to fuel new cycles of learning and growth.

AI isn’t the end of the story. It’s how you start the next chapter.