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[ARTICLE Β· art-52183] src=thetruthasiseeitnow.com β†— pub= topic=artificial-intelligence verified=true sentiment=Β· neutral

You're going to be left behind if you don't understand AI.

A new analogy compares AI to race cars, arguing that the value of AI depends on skilled users, not just the technology itself. The author suggests that companies should invest in experienced people who can effectively leverage AI, rather than distributing it broadly.

read1 min views1 publishedJul 7, 2026

A fast car doesn't win races β€” a driver does. The same is now true of AI, and it changes who gets hired.

People who can't drive don't need race cars.

Race cars get faster every year, and the newest one always costs the most.

But a fast car doesn't win races. A driver does.

Your best driver gives you a chance to win. Someone who can't drive gives you an expensive crash.

So the fastest car goes to your best driver. An F1 team is hundreds of people behind two drivers.

That's AI right now.

Every new model is a better car. The best one will always be a premium.

And it's the first of its kind: the output quality you get scales with the input quality it receives.

The output quality gets better by itself with every improvement to the car.

When factoring in the cost, the most logical direction is to not put it in everyone's hands, but only in the hands of the most experienced people you trust β€” the ones with a proven track record of winning races.

There are still reasons to hire people. But hiring people who can't drive, or don't know anything about cars, is now a poor business strategy.

Anyone can buy a fast car. Some of the fastest might be gated. Either way, the car doesn't win β€” the driver and the team behind them does.

So first, learn about the car, and how to drive.

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