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At Cincinnati WITCON 2026, we started our session with a question: in one word, how does AI at work make you feel right now? The answers filled the screen fast. Excited. Overwhelmed. Helpful. Forced. Scared. By the end, Excited and Overwhelmed were the two biggest words, side by side.
Every one of those words was in our building at some point. Some of them still are. And that's the point we came to make: AI transformation is a people transformation. In client work, nobody designs a product without first understanding the people who will use it. When AI arrived at Ingage, we had to apply that same discipline to ourselves.
Here's what our journey looked like, and what we learned about moving people from skeptics to believers.
We started before it was urgent
In 2023, before AI was a boardroom topic, a small AI Task Force started exploring. They tested the tools that were available, set an internal AI policy as a simple first step, and built a shared framework for how we'd approach it. Nothing flashy. It gave us a head start we didn't know we'd need.
In 2024, our leadership team made a deliberate choice to shift our culture toward aggressive learning. Pursue Growth and Learning is one of our core values, and that year we put real weight behind it.
Even with that head start, we hit the same challenges most organizations face: too many tools and no clear place to start, uneven starting points across the team, healthy skepticism about quality, and the reality that learning a new way of working is slower before it's faster.
The overwhelm was real
The biggest barrier we saw was paralysis. There's so much happening in AI that taking the first step can feel impossible. Our job was to make that step small enough for anyone to take.
Starting in July 2025, we carved out an hour of hands-on AI time at every company meeting for the rest of the year. There were eye rolls. That was okay. The exercises were simple, low stakes and a little silly, with prizes:
- A team prompting challenge, where everyone started from the same baseline prompt and the most creative approach won.
- An AI Creativity Challenge: one team photo, one prompt to transform it, no retries, 20 minutes.
- Vibe Designing, where groups prompted an AI design tool for a client scenario, then graded the result on usability.
Looking back, even our games kept people at the center. The Creativity Challenge rewarded teams for keeping their original photo recognizable. Vibe Designing asked teams to think through the client's needs before they prompted anything.
We were honest about the hard parts, too. When Angie tried to hand a five-minute weekly task to AI, each attempt took most of a day, and the AI eventually suggested she go learn a new automation tool. At first, AI often makes you slower. Gains come after the initial investment, and some tasks don't need AI at all. Saying that out loud gives people permission to struggle without feeling like they're failing.
We also made room for the "ick." Everyone has something about AI output that makes them cringe. At WITCON, the room's top icks were false confidence and cognitive surrender: answers that sound certain and turn out wrong, and the temptation to stop thinking for yourself. Those reactions are useful. They're a quality bar, and the people with the strongest objections often have the sharpest judgment.
Ready when it mattered
Late in 2025, the models took a big leap. A few of our technical leads walked into leadership's office with a warning: this could change our company. The models were starting to do work that looked a lot like ours.
We could have put our heads in the sand. We leaned in instead, with plenty of curiosity and some fear. Two years of groundwork and a year of hands-on time meant the advances met a prepared organization, and we could accelerate instead of scramble.
That moment also surfaced the question that usually goes unsaid: what happens to the expertise I spent years building? Most people aren't worried about a robot taking their desk. They're wondering whether the skills they worked so hard to prove still count.
What we saw is that expertise moved. Knowing what good looks like, asking the right question, and spotting when an answer is wrong became more valuable, because AI produces a lot of answers. Judgment decides which ones are good.
Learning together, owned by our people
As an employee-owned company, we remind each other that it's on all of us to help grow the organization. See a problem, fix the problem. See an opportunity, seize it. The people who raised the alarm about AI were owners, and they became the people who led us forward.
Everybody learns differently, so we offered many ways in: hands-on time, book clubs, learning mentors who paired up across experience levels, and hackathons. Nobody had to be an expert to show up.
Our people built most of it themselves. One of our technical leads started a Vibe Coding Book club. Our teams joined SW Ohio GiveCamp, building for local nonprofits, and found custom software as easy as, or easier than, off-the-shelf solutions. AI happy hours, vibe designing at the IxDA meetup, and AI 101 sessions at our shareholder meeting followed. Leadership created the time. Our people created the momentum.
One of our biggest skeptics joined the book club with real doubts, and you could hear them in the early sessions. By the end, she had built a tool to automate her own time entry and wanted to share it with the rest of the company. Nobody argued her into it. She built her way there.
Find the right problem first
The thread through all of it is the same principle we use with clients. AI makes building faster, which makes finding the right problem first matter more than ever. Understand the people. Find the real need. Then build.
What the room told us
The room's biggest barrier was know-how, at 25%, followed by trust in accuracy at 19% and time at 16%. Privacy, cost and team buy-in barely registered. People have access to the tools and want to use them; what they need is skill and confidence. That's why every step on our list below leans on hands-on practice.
The most upvoted question asked how to handle the stress of being expected to deliver more, faster. It's a fair worry, because speed gains raise expectations. Leaders decide whether saved time goes to more output or back to their people, and we'll share how we think about that in an upcoming post.
Start where you are
Every person at our WITCON session left with an AI Action Card: their biggest challenge, a few strategies to try, one thing to do in the next 30 days, and the name of someone they'll tell. If you want a place to start, pick the smallest step that fits:
- A 20-minute demo of tools your team already has.
- A simple AI policy that gives people permission.
- One hands-on hour at a meeting you already hold.
- A prompting challenge with a silly prize.
- A tool test-drive on a real problem, graded together.
- Learning mentors across experience levels.
- A book club or show-and-tell series.
- A hackathon, ideally for a good cause.
- Let whoever's curious lead the next session.
Technology decisions are people decisions. It's okay to be at step one, as long as you're taking a step.
The room also sent us 16 anonymous questions we didn't have time to answer, from protecting critical thinking to what AI means for careers. We'll take them on in a series over the coming weeks. If your organization is working through its own AI adoption, we'd love to compare notes.
