An internal initiative promoting AI adoption.
I led the design of an internal home for an enterprise AI Practice. That covers the information architecture, content strategy, and UX for a hub that supports AI agent and AI Skills work, and gives our teams and clients a real, credible place to start using AI in their everyday work.
Make AI adoption feel real for our own teams, not just something we sell externally. Build the internal home that supports our AI agent work and gives colleagues a credible, approachable place to start.
Senior UI/UX Designer leading end-to-end design of the internal AI Practice hub. Information architecture, content strategy, and the UX patterns that surface our AI agents and Skills work in a way people actually want to engage with.
A living internal hub adopted as a working reference across the organization, actively used to drive AI agent adoption and pulled into broader conversations about our AI strategy with clients.
The challenge
AI moves fast. The hard part is making it move at the speed of your own organization, too.
The company wanted an internal home for their AI practice. Somewhere their own teams could go to see what was being built, how AI agents and skills slotted into real work, and where the practice was heading next. The brief wasn't just "make a page about AI." It was: design the experience that turns AI from a buzzword into something colleagues actually pull into their day-to-day work. There was no playbook for this. We had to build one.
My job was to lead the design of that internal hub end to end. That meant figuring out the information architecture, shaping the content strategy, and designing the UI/UX patterns that make the practice make sense to the rest of the organization. It also meant staying close to what was actually landing with people and adapting fast when something wasn't working.
How I approached it
An internal product deserves the same design care as anything we'd ship externally. Our own teams are users too, and they deserve a good experience.
Information architecture
Structured the practice around how our teams actually use it. Agents, skills, and patterns up front, with the deeper "why we built it this way" content one click away.
Content strategy
Shaped what every page should say and in what order. The site reads like a confident, working reference, not a marketing page trying to sound smart about AI.
UX patterns
Designed the patterns for showing agents, skills, and use cases. Recognizable surfaces that hold up as the practice grows.
Driving adoption
Closed the loop with teams using the site. Refined the IA, the content, and the prompts that get colleagues to actually try the agents and patterns we'd built.
Decisions that mattered
Treat the internal site like a product, not a wiki
It would've been easy to ship this as documentation and move on. We chose to give it real product thinking. Clean IA, intentional content, designed patterns. Internal teams deserve the same UX care as anything we'd send out the door.
Lead with patterns, not theory
Most "AI at work" content starts with what AI is. We led with what AI does. Specific agents, specific patterns, specific use cases. The philosophy moved further down the page for the people who wanted it.
Make adoption the actual design goal
The success metric for this site isn't traffic. It's whether a colleague clicked through and actually used an agent or pattern in their own work that week. Every design decision came back to that.
What's changed
Specific examples are covered in the full case study Public highlights:
The hub is referenced daily across multiple teams and departments as the go-to starting point for AI agent and Skills work. Not a static one-pager collecting dust.
The practice site gets pulled into client conversations about our AI strategy, giving us a professional, polished way to show how we think about AI adoption.
The UX patterns I designed for agents, skills, and use cases have held up as the practice has expanded. New additions slot in without breaking what's already there.
Teams who engaged with the hub showed higher rates of actually trying the AI agents and patterns we'd built. That was the real metric we were designing toward.
What I'd carry forward
Your own teams are users too. Treating their tools with the same design care as anything you'd ship externally actually paid off here, in adoption, in credibility, and in the quality of conversations it opened up with clients.
Adoption happens when you lower the barrier to trying something today, not when you explain how exciting it might be someday. That distinction shaped almost every decision we made on this project.
The core challenge here, taking something complex and making it actually usable, is one I've been solving for 17 years. AI is new territory, but the problem felt familiar. That's probably why I picked it up fast.
Got an AI challenge? I'd love to hear about it.
I love talking about design and hard problems. Drop me a line or connect on LinkedIn. I'd genuinely love to hear from you.