We Learned How to Use AI the Right Way (And It Changed How Our Whole Team Works)
There's no shortage of opinions about AI in the workplace right now. Some people treat it like it's going to replace everyone, others dismiss it entirely. After spending real time integrating AI tools across our team—not just in one department, but across the board—we've landed somewhere much more practical than either of those extremes.
AI tools are genuinely powerful. But that power only shows up when you know how to aim them at the right things.
The Difference Between Using AI and Using AI Well
Early on, we made the same mistake a lot of teams make. We gave people access to tools and kind of assumed productivity would follow. It didn't, at least not right away.
What changed things was getting specific about where AI actually helps. Not trying to make it do everything, but figuring out the tasks where it genuinely saves time and does them well. Once our team started treating AI as a focused assistant rather than a magic button, the results were night and day.
The key insight was pretty simple: AI is at its best when you point it in a clear direction. A vague ask gets you a vague result. A specific, well-framed task—summarize this meeting, draft captions for these posts, pull together research on this topic—gets you something you can actually use.
What AI Actually Does for Our Team
Across our team, AI handles a lot of the work that used to quietly eat up everyone's time. Not the work that requires creative judgment or a human touch, but the stuff that sits between you and that work.
Meeting notes and summaries. Instead of someone spending 30 minutes after a call writing up what was discussed, AI handles the summary. The team reviews it, makes adjustments, and moves on. That time goes back into the actual work that came out of the meeting.
Research and background work. When we need to get up to speed on a topic, understand a market, or pull together context for a project, AI does the initial heavy lifting. It gathers, organizes, and summarizes so that the team can focus on analyzing and making decisions rather than just collecting information.
Content support. Drafting captions, writing first passes on copy, repurposing content across formats—these are tasks that used to take more time than they probably should. AI handles the initial draft, and our team shapes it into something that actually sounds like us and fits the context.
Documentation and write-ups. Reports, briefs, internal docs—the things that are important but always seem to get pushed to the bottom of the list because they're time-consuming. AI takes the pain out of getting a first version together, which means these things actually get done instead of getting skipped.
None of this replaces the people doing the work. It just removes a lot of the friction that used to sit in between them and the work that actually matters.
The Boring Labor vs. The Human Labor
This is the framing that made things click for us. There's work that needs a human touch—the judgment calls, the creative decisions, the relationship-building, the strategy. And then there's the labor that surrounds it: the organizing, the summarizing, the formatting, the first drafts, the research gathering.
AI is really good at that second category. Not perfect, but good enough that it frees people up to spend more of their time on the first category. That's where the real value is. Not in replacing people, but in making sure people spend their hours on the things only people can do.
When you frame it that way, the ROI becomes pretty obvious. You're not paying for a tool that does your team's job. You're paying for a tool that clears the path so your team can do their job better and faster.
It's Not About Whether You Should Use AI. It's About What You Use It For.
Tools in the workplace have always been evolving. Every time a new category of tool shows up, there's a version of the same conversation—should we use this, will it replace something, is it worth learning. And every time, the answer ends up being the same: it depends on what you use it for and what the trade-offs are.
AI is no different. It's not a question of whether your team should be using it. It's about understanding where it fits, what it's good at, and where it still needs a human in the loop. The teams that figure that out are the ones that get the most out of it.
The group of tools we use just evolves over time. That's always been the case. What matters is being thoughtful about where each tool adds value and where it doesn't.
What We've Learned
After going through the process of actually integrating AI into how our team works, a few things stand out:
Give it direction. AI performs best when the task is clear and specific. The more context and direction you give it, the better the output. Treat it like you're briefing a capable assistant, not making a wish.
Keep humans in the loop. AI drafts, humans decide. That's the workflow that works. The output is a starting point, not a finished product.
Invest in the learning curve. It takes a bit of time for people to figure out how to use these tools effectively. That time is worth it. The productivity gains come after people develop a feel for what works.
Not everything needs AI. Some tasks are faster to just do yourself. Knowing when to reach for the tool and when not to is part of using it well.
Where We've Landed
AI hasn't replaced anyone on our team. What it has done is take a lot of the repetitive, time-consuming work off their plates so they can focus on the things that actually require their expertise and judgment.
The result is a team that moves faster, produces more, and spends less time on the parts of the job that nobody enjoys but everyone used to accept as unavoidable.
For any organization still figuring out where AI fits, our honest advice is to start with the boring stuff. The summaries, the drafts, the research legwork. Let AI handle that, let your people handle the rest, and see what happens. We think you'll be surprised at how much of a difference it makes.