Why AI Needs a Label Maker: Design as the Key to Adoption
- 1 day ago
- 2 min read
In the early days of Microsoft, new hires like me were shipped off to Franklin-Covey seminars to learn time management. We got leather-bound binders with daily calendar inserts, and one section asked you to write titles on tabbed pages.
The instructor gave us a choice: scribble the labels in pen (fast, free, and done) or buy a $100 professional label maker. Back then, $100 for labels felt like highway robbery.
Why bother?
His answer stuck with me: when something looks professional, people take it more seriously. Researchers now call this the aesthetic-usability effect and processing fluency theory, fancy names for a simple truth: good design makes things feel easier, more valuable, and more trustworthy.
So What Does This Have to Do with AI?
The same principle applies to artificial intelligence. Today, companies are pouring millions into AI proofs of concept, but over 97% never make it to production.
Why?
Because while the models work, the experience doesn’t. Employees won’t adopt AI tools that look like DMV paperwork stapled to a spreadsheet.
This is why partnering with technically brilliant AI developers isn’t enough anymore. The best partners don’t just build brains; they dress them well. They understand that design is not decoration—it’s the front door to adoption.
Run a Google Image search for “Power BI report” and you’ll see the problem. Page after page of nearly identical dashboards: grey grids, boring tabs, maybe a different shade of blue if you’re lucky. The AI insights might be gold, but the delivery is beige.
What Great AI Partners Do Differently
Successful AI adoption requires more than technical brilliance. With design as the front door to adoption, we create dashboards and reports that are as intuitive as possible, and we channel the spirit of that $100 label maker.
Our designs feature:
Custom buttons in the report margins instead of the same old Power BI tabs.
Rounded corners everywhere—except for filters, which are square, post-it yellow, and impossible to miss.
Logical groupings in containers so every section has a clear purpose.
Explanatory text at the top-left, because that’s prime real estate for English readers.
Subtle 3D shading to guide the eye—filters pop, data follows.
Primary colors for top metrics, muted tones for context.
Bright yellow highlights for what’s currently selected, so users never get lost.
The Bottom Line
AI adoption isn’t blocked by bad math; it’s blocked by bad design. If you’re paying a partner to build AI, make sure they don’t just deliver the model. Feuji ensures your AI tools deliver the experience your teams actually want to use. A dashboard that engages, guides, and even delights your employees will do more to drive adoption than a 50-page white paper ever could.
In other words: don’t settle for pen-scribbled tabs. Get the label maker.
