Challenge

Licenses alone don't unlock AI — context does

Rolling out AI meant more than handing out seats. The real unlock was context — and our best context was sitting unused in forgotten docs and decks.

When we rolled out AI at AXS, I didn't want to hand out licenses and hope for productivity. My team's experience with AI varied, and I knew the power came from giving AI context, not from teaching prompt engineering.

And every team already had that context: docs and decks. The ones we pour time into making, presenting, and circulating, only to forget a week later. New team members got a wall of information on day one and forgot most of it by week two.

Finding a doc meant tracking down whoever had the link and waiting, sometimes for days. Then came the real work: reading it, finding the part that applied, and interpreting it.

Solution

Turn process docs into GPTs — a 24/7 coach for the team

Diagram of AI agent capabilities for writing, thinking, researching, collaborating, and synthesizing

Prompt engineering fades. Context doesn't. I turned our docs into purpose-built GPTs so everyone could work from the same level of quality.

Context is why I can say less to my best friend and still be understood — we share history. Context gives AI that history from day one.

Using Projects and GPTs for my own hobbies felt like having a 24/7 coach, with the shorthand of an old friend.

Our GPTs included a UX copywriting expert trained on our voice and tone, a research assistant covering planning through synthesis, and a Career Coach built on our Career Ladder.

The goal was never to replace the work. It was to raise the floor on everyone's output. That's what makes the way I like to roll out AI empowering instead of threatening.
Results

Hours saved, new skills, and company-wide adoption

Survey results charts showing strategic thinking, brainstorming, time savings, and quality improvements
9purpose-built agents built by my team
$200k+Annual retainer saved on UX copywriters
100%Design team adoption

Hours — sometimes days — saved. The team pitched their own GPT ideas, and after I ran a workshop on AI and agents, other teams across the company followed.

We were the first team at AXS to work this way, so I tracked usage with a bi-weekly survey. Beyond the time saved, people said they'd picked up new skills, and we built and shared the GPTs they pitched.