Talk Is Cheap

History tends to repeat itself, so this week, let's take a look at the archives…

In the early 1900s, governments and top universities were in a race to invent the first flying machine. They held meetings, wrote papers, made big promises — and spent a lot of money talking about it and planning for it.

Meanwhile, two brothers in a bicycle shop in Ohio were quietly working on their own version. The Wright brothers built and tested hundreds of small prototypes. They didn't wait for perfect conditions or outside approval — they just kept trying, learning, and improving.

And in 1903, they flew. While others were still talking about how flight might work, they actually made it happen.

1902. The beginning of a glide.

The first airplane didn't come from a government lab or a high-powered team. It came from a small workshop, a lot of determination, and a willingness to do the hard thing: build.

If we fast forward to today and swap flight for AI, not much has changed. While everyone's busy talking about it, only a few are doing the actual work of building with it.

These are the real reasons implementation is lagging:

1. The Problem Isn't AI — It's the Setup Around It

It's not that AI doesn't work. It's that most companies aren't ready for it.

• Their data is a mess — scattered across spreadsheets, siloed tools, and teams that don't talk to each other.
• Their systems are outdated — still running on slow, clunky infrastructure instead of modern cloud setups that can actually support AI tools.

You can't plug AI into chaos and expect results. You need someone to organize and make sense of the raw data first before you can get results, and that scares people.

2. People Are Quietly Blocking It

People think that AI threatens their jobs. So guess who's slowing things down?

• Middle managers — who see AI automating the work below them, and start worrying about their own job security.

• HR — worried about layoffs or disruption, quietly throwing up roadblocks.

• Compliance teams — concerned about risk, privacy, and liability, saying "not yet" over and over.

The tech doesn't stall. The people do.

3. Lawyers, Uncertainty, and Red Tape

Even when the business wants AI, the legal side has a tendency to drag it down. Lawyers aren't usually rewarded for taking risks.

• No clear rules around AI usage = risk.
• No legal precedents = more risk.
• Anything involving data, fairness, or automation = even more risk.

So the default decision becomes: "Let's wait."

Mind the gap

There's a massive gap between the buzz and the build.

Mark Cuban said it best:

"Ive been through every single technology event and evolution and this blows them all away...Learn all you can about AI, but learn more about how you can implement [it] in companies. We got the Head of Microsoft saying software is dead because everything is going to be customized to your unique utilization. Who's going to do it for them?"

And he's right.

Every exec is raving about AI on panels and podcasts. But inside their companies? Things are mostly status quo.

According to the Economist, only around 10% of firms are using AI in any meaningful way.

The Real Opportunity

Don't just read about AI. Implement it.

The companies that win in this era won't be the ones with the biggest models, the most strategy meetings, or fanciest decks.

They'll be the ones who figure out how to actually use AI — inside their messy orgs, with all the human and technical baggage that comes with it.

Be the person who can walk into a company, make sense of the chaos, and ship something real.

Or let us help you.

We've dealt with messes way bigger than yours.