For a long time, I thought the hardest part of AI was understanding it. The acronyms, the models, the benchmarks. Then I read a post from an AI professional that turned that idea upside down.
The author makes a simple point. Almost nobody knows what “GPT” stands for (it’s Generative Pre-trained Transformer, if you’re curious), and it doesn’t matter at all. What matters is whether people at your company actually use AI. And according to this expert, most businesses don’t get there by learning more terms. They get there with a roadmap with clear targets.
This comes from someone who has spent real time on the problem. The creator grew the newsletter How to AI to 1,000,000 readers. After that, they spent 8 months quietly studying one question: why is AI adoption so hard for real businesses? What they found is worth a few minutes of your time.
The problem: AI is overhyped, underestimated, and overwhelming
The original poster sums up the adoption struggle in three parts:
- It’s overhyped. You keep hearing it’s like having a Nobel Prize winner in your pocket, and then you can’t get it to work.
- It’s underestimated. Most businesses pay for AI tools, but hardly anyone on the team uses them.
- It’s overwhelming. New models, new tools, and a whole new way of working show up “every freaking Tuesday.”
That second point hit me hardest. Plenty of companies have the licenses, the logins, and the budget line. What they don’t have is people who open the tool on a normal Monday and get real work done with it.
The solution: a roadmap before tools
So what’s the fix? The expert’s answer is refreshingly grounded. You don’t need to turn into an overnight “AI company.” You need a plan that shows where AI fits in your business and what success looks like.
The approach this LinkedIn creator describes has four stages: train, adopt, deploy, and maintain. That last one matters. AI isn’t a one-time install. Tools change constantly, so someone has to keep things running and keep people up to speed.
The companies already doing it
Here’s where the post gets really concrete. The author shared the kinds of businesses working with their team, and none of them are Silicon Valley startups:
- ☑ Bal Seal Engineering: makes parts for the Artemis rockets, 350 employees.
- ☑ Velocity One: an aerospace and defense company that went to Mars (with the Rover), 600 employees.
- ☑ Bjerk Builders: commercial construction since 1986, 85 employees.
- ☑ Phoenix Heat Treating: a commercial metal-treating plant serving clients like SpaceX, 70 employees.
I love this list. These are hands-on, precision-heavy companies with 70 to 600 people. They’re not chasing hype. They want AI to help them do their jobs, and that’s exactly the audience the post’s author is focused on: people who want to benefit from AI without reinventing their whole identity.
How to apply this in your own team
You can borrow this thinking even if you’re starting from zero. Here’s how I’d turn the expert’s insight into action:
- Set two or three clear targets, like “cut quote prep time in half” or “draft every client email with AI first.”
- Check who actually uses the AI tools you already pay for, and ask the rest what’s stopping them.
- Train people on their real daily tasks, not on how the technology works.
- Ignore the weekly flood of launches unless one directly helps a target you’ve set.
- Assign someone to maintain it, so tools, prompts, and habits keep up as things change.
The big lesson for me is that adoption is a people problem, not a tech problem. If rocket-part makers and metal-treating plants can make it work, a marketing team or a small agency definitely can.
The mission behind it
The person who shared this ended with a note I found moving. Their goal is to help 1,000,000 people use AI confidently at work.
“Because I don’t want 1 million people to wake up one day and feel so left behind they stop caring.”
That’s the real risk here. It isn’t that AI replaces you overnight. It’s that the pace wears you down until you check out. A simple roadmap with clear targets is the fix for that feeling.
Check out the full LinkedIn post to see the video and the author’s complete take on AI adoption.