Brett Wooden, Financial Institution Software Strategist, Buildable
I use AI every day. I use it to bounce around ideas, challenge my thinking, research topics, work through problems and turn rough thoughts into something useful. There are days when I can spend hours working alongside AI and walk away feeling like I accomplished a ton. And I probably did.
But I’ve also started noticing something about those days. I can have what feels like conversation after conversation with AI. I share an idea, ask a question, push back on an answer and work through a problem. It feels collaborative, and in many ways it is. Yet sometimes I get to the end of the day and realize that nobody actually heard any of those ideas. I may have been incredibly productive, but I wasn’t necessarily connected to anyone while doing it.
That has made me think differently about one part of AI adoption that I don’t believe we’re talking about enough. I’m certainly not advocating that we use less AI. I spend a lot of my time helping credit unions and their leaders understand how to use it better. I believe this technology can make us dramatically more productive and help people do work they couldn’t have done on their own just a few years ago. The question is whether leaders are also paying attention to what might quietly disappear as AI becomes part of nearly everything we do.
Harvard Business Review has been tracking how people use generative AI, and the uses have become increasingly personal. In its 2025 analysis, the research found people were using AI across both personal and professional needs, including as a sounding board, advisor and source of support. That makes sense to me because one of the best things about AI is that it is always there. I can ask a question without worrying about interrupting someone. I can throw out an idea that isn’t fully formed, ask what might be a stupid question or challenge an answer five different ways without worrying that I’m annoying the person on the other end.
That is incredibly useful. But it also raises a leadership question: What happens when AI starts taking the place of conversations that previously happened between people?
The Conversations Behind the Work
Think about how often someone at work used to say, “Can I bounce something off you?” Maybe it was, “Can you take a look at this?” or, “I’m stuck. What would you do?” Those conversations may seem small, especially when we’re measuring productivity, but I’m starting to believe they are a much bigger part of how organizations work than we realize.
I work remotely, so I don’t believe this is an office-versus-remote-work issue. At Buildable, I regularly jump on Teams with our engineers, designers, our owner and other members of our team. Sometimes I call because I have a question. Sometimes someone calls because they want my thoughts on something they’ve created. Other times I just want to see what they’re working on.
One of my favorite things is talking with a senior engineer and listening to them explain something they’re building. I may understand the business problem, but they understand the engineering behind it at a level I don’t, and I learn something almost every time. I have the same experience when one of our UX/UI designers walks me through something they’ve created. I ask questions, they explain why they approached something a certain way, we might disagree on something and eventually land on a better idea. Sometimes another person gets pulled into the conversation. Sometimes we’re troubleshooting something, and sometimes we’re just laughing along the way.
There’s value in the work that comes out of those conversations, but there’s also tremendous value in the conversation itself. As a leader, that’s where I learn how people think. You start recognizing who sees a problem nobody else noticed, who can take something very technical and explain it simply, who asks great questions or who has a skill you didn’t realize they had. You learn what kind of work excites people and where someone might be ready for a bigger opportunity.
Leaders often discover talent while the work is being created, not simply when the finished product lands in front of them.
That’s part of what I worry we could lose. If someone runs into a problem, works through the entire thing with AI and hands me a polished final answer, I get to see the result. What I may not see is how that person approached the problem, the questions they asked, where they got stuck or what they learned along the way.
There’s a broader organizational issue here too. Not that long ago, someone struggling with a problem might have asked the person next to them. That person might not know the answer, so they pull someone else into the discussion. Eventually three people are standing around working through it. It may not look like the most efficient way to get an answer, but three people just learned something.
Today, an employee can ask AI, get the answer in seconds and move on. That is an incredible productivity improvement for the individual, but unless that employee intentionally shares what they learned, the knowledge may never spread beyond that conversation with AI.
Microsoft researchers recently found something that makes this worth watching. In a 2026 study of workplace generative AI usage, heavy AI users showed increases in both productivity-oriented activity and communication, but productivity activity increased much more, 21.2% compared with 7.1% for communication activity. The researchers noted that the shift was toward more individual, documentation-focused work and raised the importance of ensuring AI adoption doesn’t weaken interpersonal communication or the flow of information that supports innovation.
That doesn’t mean AI is making everyone isolated. It does suggest the way work happens is changing, and leaders should understand what that change means for their teams.
Are We More Polished, But Harder to Know?
I’ve started noticing another version of this in my email.
I receive a lot of messages now that were clearly written or heavily cleaned up with AI. There’s nothing wrong with that. I use AI to help with emails too. But every once in a while, I’ll read an email that is professional, formatted perfectly and says all the right things, yet I have a harder time understanding where the person is actually coming from.
The communication is better, but somehow I know less about the person communicating.
I think there is a meaningful difference between telling AI, “Help me communicate what I’m trying to say more clearly,” and simply saying, “Write this email for me.” One uses AI to improve our communication. The other can start replacing our voice entirely.
For leaders, that matters. We don’t need people intentionally adding typos to prove they wrote something themselves, and there is no reason to reject a tool that can help someone communicate more clearly. But I also don’t want every person I work with eventually sounding exactly the same. I want to understand what they think, how they see a situation and why something matters to them.
AI should help people communicate their thinking. We should be careful that it doesn’t slowly hide the thinking itself.
What Are We Doing With the Time AI Gives Back?
All of this also connects to something I hear constantly from people in the credit union industry: people are overwhelmed. There is another meeting, another email, another project, another system and another priority competing for attention. AI is supposed to help us with some of that, and the early research suggests it can.
A field experiment involving 7,137 knowledge workers across 66 companies found that employees who actually used the generative AI tools provided to them spent about two fewer hours per week on email and reduced the amount of work they did outside normal working hours. That’s exactly the type of outcome many of us hope for when we talk about AI creating efficiency.
But it creates another question for leaders: What are we going to do with the time AI gives us back?
If a person can accomplish in six hours what previously took eight, do we immediately find another two hours of work for them? If someone can produce five reports in the time it used to take to create three, does five simply become the new expectation? Do we keep filling every available minute until employees are producing dramatically more but somehow feel just as overwhelmed as they did before?
There’s another option. Some of that capacity can go toward things that have always been difficult to measure: mentoring someone, learning a new skill, talking with members, brainstorming with coworkers, thinking about a problem instead of immediately reacting to it, or calling someone on Teams and asking, “What are you working on?”
AI doesn’t automatically create capacity inside an organization. Leaders decide what happens to the capacity AI creates.
That may become one of the more important leadership decisions surrounding AI. Credit unions are rightfully spending time thinking about governance, security, privacy, data, policies and training. Those things matter, and they aren’t going away. I think human connection needs to become part of that conversation too.
That doesn’t require another policy. It may be as simple as continuing to create opportunities for people to show each other what they’re working on. If someone discovers a great way to use AI, have them share it instead of leaving that knowledge inside their own chat history. Keep some brainstorming sessions human. Ask people how they got to an answer instead of only reviewing the answer. Let AI improve communication without polishing every individual voice out of it.
And perhaps most importantly, don’t automatically fill every minute AI saves with another task.
Some of the most valuable parts of work are also some of the hardest things to put into a productivity report. They are the conversation that unexpectedly produces a better idea, the question that helps you discover how much someone knows, the laugh in the middle of troubleshooting something and the employee who calls and says, “You need to see what I built.”
I love AI and I don’t see myself going backward. I love being able to bounce an idea off it almost any time I want and get immediate feedback. It has changed how I work.
But I also love calling one of our engineers and hearing the excitement in their voice when they explain what they’re building. I love watching a designer walk me through something they’ve created and asking why they made certain choices. I like asking questions and learning from people who know things I don’t.
Those conversations aren’t inefficiencies we need to eliminate. They’re part of how we learn about each other, develop people and build a team.
AI can absolutely help us become more productive. The leadership challenge is making sure we don’t become less connected in the process.
If you are thinking through these tradeoffs or looking to move from ideas to execution, Buildable can help. You can reach me at bwooden@buildableworks.com for the opportunity to connect and share what we are seeing across the credit union and fintech space.
Harvard Business Review. “How People Are Really Using Gen AI in 2025.” April 2025. https://hbr.org/2025/04/how-people-are-really-using-gen-ai-in-2025
Microsoft Research. “Adoption of Generative AI in the Workplace: Increasing and Shifting the Balance of Productivity and Communication Activity.” 2026. https://www.microsoft.com/en-us/research/publication/adoption-of-generative-ai-in-the-workplace-increasing-and-shifting-the-balance-of-productivity-and-communication-activity/
National Bureau of Economic Research. “Generative AI at Work.” NBER Working Paper. https://www.nber.org/papers/w33795