Natalia Quintero wrote about what she’s learned from talking to more than 100 companies about AI implementation. This part about the problem with early adopters and isolated workflows stood out:
AI doesn’t spread like other software. Think about Asana. If one person decides to organize their team’s tasks there, everyone benefits automatically because the work is more organized, and someone on the team has taken responsibility for that organization. You don’t need to learn the tool to get value from your colleague using it. AI doesn’t work that way. If you develop workflows around how you work, that value doesn’t automatically translate to the rest of the company. Your prompts, your GPTs, your automations—they’re built around your context, your processes, and your way of thinking. They don’t transfer.
That’s the adoption problem in a nutshell. A power user’s AI setup is like their personal note-taking system—valuable for them but not portable. It explains why enterprise rollouts don’t work the way everyone expects.
The recruiting firm example is good: they trained 10 champions who built tools their peers wanted to use. One person automated scheduling coordination (saving 2–10 hours per task), and suddenly 30 others got curious. Peer-to-peer beats top-down mandates.
(If you’re curious about my setup, I wrote about it here)