AI shouldn’t replace our learning, but instead accelerate it.

I’ve been learning about artificial intelligence for a little over a year and a half now. And the more I learn, the clearer one thing becomes: we talk a lot about what AI can do for us, but maybe not enough about what it can help us learn.

Yes, there is hype. A lot of it. There is also fear. And I don’t think that fear is completely unjustified. It’s obvious that, with artificial intelligence, many companies will be able to do more with fewer people. Productivity is going to change. The way we work will change too. And many repetitive, operational, or low-value tasks will be automated.

But there is another part of the conversation that interests me much more.

Recently, I listened to a reflection by Jensen Huang, CEO of NVIDIA, that really made me think. He basically said that companies that truly know how to take advantage of the power of AI won’t necessarily fire people, but will instead find new ways to place them, empower them, and make better use of their talent.

And I think that’s one of the key ideas.

AI can take repetitive work away from us, yes. But it can also give us back something far more valuable: time to learn, think better, and develop judgment.

Learning with AI: from searching for content to building your own path

Let me give a personal example.

Lately, I’ve been very interested in learning about SEO and Answer Engine Optimization. Mainly because I’m increasingly convinced that the way a brand appears, is mentioned, or is recommended in artificial intelligence environments will become more and more important.

It’s no longer just about appearing on Google. It’s also about existing in the answers given by AI models.

In our case, at TOTEM Branding, this is highly relevant. If we work with brands, strategy, positioning, and visibility, we need to understand how the way people discover, ask, compare, and choose is changing.

So I started looking for SEO courses. I found several options, some of them very good. But the more I researched, the more I realized that SEO is huge. There are too many branches, too many layers, too many approaches.

Technical SEO. Keywords. Web architecture. Content. Authority. Link building. Search intent. Analytics. Performance. GEO. AEO. And I could keep going.

The question I asked myself was quite simple:

What do I need to learn about SEO that is truly useful for my life, my projects, the company, and our clients?

That question changed everything.

Instead of adapting myself to a generic course, I decided to try the opposite: creating a course adapted to me.

How I used AI to design a personalized course

The first thing I did was ask AI to help me structure what I should learn about SEO from a practical perspective.

I didn’t want to become a purely technical specialist. I wanted to understand enough to apply the knowledge to real projects, make better decisions, spot opportunities, and connect SEO with brand, content, and artificial intelligence.

Then I asked it to identify the best free platforms and resources to learn each part. It recommended very strong and well-organized resources. Honestly, I was pleasantly surprised by the quality of the response.

But the problem was still there: there was too much content.

I could have thirty useful SEO sections in front of me, but if I tried to learn everything in depth, I would probably need a full year dedicating one hour a day to it. And that wasn’t my goal.

So I went one step further.

I asked AI to prioritize. To tell me which parts were the most important, which ones were complementary, and which had the highest impact for my specific case.

That’s when something much more interesting started to appear: a personalized learning map.

It wasn’t “learn SEO.” It was:

learn this first, because it helps you with this; then learn this other thing, because it complements it; and leave this for later, because right now it’s not as critical.

That nuance is huge.

From a learning structure to my own platform

With that foundation, I took the experiment a little further.

Some of you may already know Claude Code, a tool that is becoming very popular both among developers and among people who don’t necessarily know how to code in depth, but want to build products, prototypes, or tools with the help of AI.

What I did was ask it to build me a small learning platform.

A kind of personal course, step by step, with everything that, for me, a good learning module should have:

• daily objectives,
• key concepts,
• free resources to go deeper,
• practical tasks,
• quizzes,
• checklists,
• areas to reinforce,
• measurable progress.

The result was a 21-day SEO course adapted to what I needed to learn.

Was it perfect? Probably not.

Did it need some adjustments? Yes.

But the important thing wasn’t perfection. The important thing was the shift in logic.

Until now, we were usually the ones who had to search for content and adapt ourselves to it. Now we can begin to make content adapt to us, to our context, to our goals, and to the way we learn.

To me, that feels like a silent revolution.

The real risk is not that AI learns for us

I’m sharing all this because I see an interesting contradiction.

On one hand, many people are afraid that AI will replace human skills. On the other hand, those same people are starting to think they no longer need to learn certain things because “AI already knows them.”

And I think that’s where the mistake is.

If we let AI hold all the knowledge, we will also be allowing it to hold more and more of the judgment.

And when we lose judgment, we become much more replaceable.

For me, artificial intelligence should not be an excuse to stop learning. It should be exactly the opposite: a tool to learn faster, better, and with greater ability to apply what we learn.

The difference lies in who sets the direction.

We can use AI as if it were the captain of the ship and simply obey. Or we can understand it as a very powerful crew: capable of rowing, raising the sails, checking maps, detecting routes, and accelerating the journey.

But the captain should still be us.

Knowing is no longer enough. We need to know how to act

Even before AI, we were already living in an incredible time for learning. The internet, YouTube, books, courses, newsletters, podcasts. The information was there. A lot of it. Almost infinite.

But precisely because of that, the problem was no longer just accessing knowledge. The problem was knowing what to do with it.

With AI, that difference becomes even more important.

The value is no longer only in knowing. It is in knowing how to ask, how to connect ideas, how to prioritize, how to apply, and how to turn knowledge into action.

That’s where I believe AI can be truly powerful.

Not only as a tool to automate tasks. Also as a new way of interacting with knowledge.

A more personalized, practical, and actionable way.

AI as a driver of personal learning

What excites me most about this stage is not that AI can do things for me. That’s useful, of course. We all benefit from removing repetitive tasks or speeding up processes.

But what I find truly powerful is that it allows us to learn in a different way.

We can build our own courses. Create simulators. Ask for explanations adapted to our level. Turn complex topics into action plans. Practice. Evaluate ourselves. Compare approaches. Build tools that, until recently, only technical profiles could create.

And all of this changes our relationship with learning.

We no longer depend only on finding the perfect course, the perfect teacher, or the perfect piece of content.

We can build our own path.

But for that, we need something AI cannot provide for us: intention.

We need to know what we want to learn, why we want to learn it, and how we want to apply it.

Because without direction, AI only accelerates the noise.

Conclusion

I believe we are entering a stage in which learning will be more important than ever.

But not learning just to accumulate information. Learning to think better. To decide better. To work better. To create better.

AI can replace some tasks, yes. But it can also greatly enhance those who have curiosity, judgment, and the desire to improve.

For me, the question is no longer only:

What can AI do for me?

The more interesting question is:

What can I learn with AI that would have taken me much more time, energy, or resources before?

That’s where I believe a huge opportunity begins.

And perhaps that is one of the great differences between using AI and truly taking advantage of it.

If you want to see how I put this into practice day to day, I go into more detail in there's no perfect AI: what really matters is starting to experiment.