I probably have not written a full line of code without AI help in more than two years.

I use ChatGPT and Claude almost every day.

But I think the companies behind them are setting us up for a trap. Maybe the biggest one in tech right now.

If you are a data analyst using AI every day, you might be walking straight into it.

Here is what I mean.

The Free Ride Is About To End

Every time you send a message to Claude or ChatGPT, these companies are losing money. A lot of it. Some estimates say the real cost may be up to 70 times higher than what users pay.

That means you're getting way more than you're paying for. These companies are burning hundreds of millions of dollars to get you hooked. To get me hooked.

And the free ride is starting to end.

Electricity prices in the US have jumped 50% in the last five years. Running these AI models is getting insanely expensive. And with rumors of OpenAI and Anthropic going public, investors will soon demand real profits. Prices will have to go up.

Think about it. What happens when a data report that costs $10 to generate today suddenly costs $700?

Would you still pay for it? Would your company?

Now imagine your whole workflow depends on AI. Every query, every chart, every decision. Then access gets cut, or the good model gets too expensive, right in the middle of an important project.

Can you still do the work?

We're already seeing companies react.

• Uber blew their entire year's AI budget in one quarter and had to cap employee usage.

• Microsoft cut AI access for some engineers to save money.

If big tech is feeling the squeeze, small teams and solo analysts will feel it even more.

AI probably isn't going anywhere. We will be using it in the future. But there's a risk in becoming so dependent on it that you cannot work without it.

Three Rules For The Smart Data Analyst

None of this means you should quit using AI. That would be a huge mistake. AI is here to stay, and you need to keep practicing with it. But you must protect yourself in three ways:

1. Keep your fundamentals sharp

You do not need to memorize every SQL command or Python function. But you should understand the logic behind the work.

Know how joins work. Know why duplicate rows appear. Know how filters can change your totals. Know what your code is trying to do before you run it.

AI can produce a clean answer that is completely wrong.

If you do not understand the basics, you will not know when the answer is wrong. You might hand bad data over to your boss or client without even noticing.

2. Do Some Work Without AI

You should be able to complete the core parts of your job on your own.

Once in a while, build a report by hand. Write a query without autocomplete. You do not need to work without AI every day, but you need to do a few AI-free reps.

This keeps your muscle memory alive so you are never helpless.

3. Know when AI is actually worth it

Not every task needs the smartest model or a 20-step AI agent.

Use AI heavily when it saves real time or helps you solve something hard. But don't spend 20 minutes prompting AI to do something you could finish yourself in fifteen.

The goal isn't to use the most AI. The goal is the best result with the least waste.

So use AI. Learn it. Get good at it.

Just do not let it become the only reason you can do your job.

Because the moment the cheap AI goes away, the analysts who can still work without it are the ones who will be fine. Everyone else is going to have a rough wake-up call.

Stay sharp out there.

P.S. Inside The Accelerator, we teach the core skills behind the tools, then show you how to use AI without letting it do all the thinking for you.