AI is making content cheaper. The human perspective is gaining value.

A few years ago, it was difficult to produce a good article.

It was necessary to know the subject. It was necessary to research. It required sitting down and thinking, reading different sources, developing an argument, writing, revising, and sometimes working on the text for days.

Today, if you place an AI tool on the same table, you can generate ten different headlines, three different article drafts, a LinkedIn post, carousel text, and a video script in just a few minutes.

This is a remarkable increase in productivity.

But it brings with it an interesting economic consequence:

The cost of content creation is decreasing dramatically.

And when the cost of producing something decreases, its supply usually increases.

That's exactly what we're experiencing.

More articles.

More LinkedIn posts.

More videos.

More newsletters.

More “Leadership in 5 Steps”.

More “top 10 skills of the future”.

A more professional-looking image.

More perfect sentences.

But are we generating at the same rate as well?

I'm not sure about that.

In fact, I think one of the most important communication paradoxes of the next few years will occur right here:

As AI reduces the cost of content creation, the value of a reliable human perspective will increase.

A study published by Gartner in September 2026 provides one of the first strong signals of this change. In the study of 1,006 consumers in the US, 65% of participants believe brands are using too much AI-generated content in their marketing efforts. 57% say that AI-generated content reduces their trust in brand messages. Even more interestingly, 43% state that they are turning to "real people" more for shopping information and advice due to the increasing prevalence of AI content. Since the study only included US consumers, it would be incorrect to generalize this to the whole world. However, it is an important signal for understanding the direction of this trend.

In a smaller study conducted by Gartner in June, 49% of US consumers believed that generative AI was degrading the quality of accessible content. This figure rose to 57% among Gen Z and millennials.

It's important not to draw the wrong conclusions here.

This data doesn't mean people are rejecting AI.

I don't think so either.

AI creates extraordinary value in content creation. It can accelerate research, compare different sources, test arguments, improve language quality, and make it easier to transform an idea into different formats.

The problem isn't using AI.

The problem is confusing AI-driven creation with simply having an idea.

Because one of the things AI does exceptionally well is generating averages.

He knows the common patterns in thousands of management articles. He knows which words related to leadership come together. He knows how strategy articles begin, which sentences grab attention on LinkedIn, and which metaphors are frequently used.

Therefore, the result is rarely a bad text.

On the contrary.

The resulting text is extremely well-written.

And that's where the problem begins.

Because in the future, bad content may not be our main problem.

Similar, good content can be a much bigger problem.

Everything is written correctly.

Everything seems correct.

Everything is professional.

But nothing stays in your mind.

You read it, and thirty minutes later you can't remember who wrote it.

Because there are sentences, but no experience.

The information is there, but there's no risk-taking approach.

There's a summary, but no reasoning.

There's content, but no people.

The explosion in AI-powered video production in China makes this supply dynamic much more visible. According to Reuters, in the first half of 2026 alone, more than 221,900 AI-generated programs were published on Douyin; however, only a small fraction of these garnered significant attention. Technology is dramatically reducing the marginal cost of production while simultaneously flooding the market with content.

This reminds me of a very basic principle of economics.

When something becomes abundant, its value shifts to something else that is scarce.

The internet has made access to information cheaper.

With the abundance of information, attention span has become scarce.

Social media has democratized broadcasting.

With the abundance of publications, distribution became scarce.

AI, on the other hand, is democratizing content creation.

I think in this abundance of content, the new scarce resource will be reliable reasoning .

We will want to know not only what a person knows, but also what they believe.

Therefore, the question also changes in terms of thought leadership.

Before:

"Do you produce content regularly?"

It was important.

Now everyone can produce content regularly.

"What do you write about?"

The value of that question may also decrease.

AI can generate reasonable articles on almost any topic.

The more pressing question becomes:

What is it that you see in this matter that others haven't quite grasped yet?

This is where thought leadership begins.

Thought leadership is not about transferring information.

Interpreting information means making connections between two developments that others haven't yet made, challenging mainstream opinion when necessary, and putting your own credibility behind a particular thesis.

AI can help you.

But he cannot be the owner of the opinion.

Because the cost of a genuine perspective isn't tokens.

It's an experience.

That's a mistake.

It's about working with customers.

It means making the wrong decision.

It means testing an idea for years.

It's about seeing different sectors.

Sometimes, it means taking the risk of saying the opposite of what the majority says.

And most importantly, when what you said turns out to be wrong, your name will still be listed under that document.

AI can write a sentence. But only a human can give that sentence its due credit.

I think it's important not to misunderstand the concept of "human-generated content" in the upcoming period.

Human-written content does not mean content written without the use of AI.

This distinction will become increasingly meaningless.

A good writer can conduct research with AI.

An academic can use AI to search through hundreds of articles.

A consultant can have AI test the counter-arguments to their own argument.

A CEO could use AI to create a first draft of their speech.

I don't see a problem with any of these.

Conversely, not using it can often create unnecessary inefficiency.

We should look for human contribution not in the tool used, but in the ownership of the idea .

I would ask these four questions:

Has this person actually experienced something like this?

Is he drawing his own conclusions from the evidence he has?

Does he clearly state the limits of his claim?

And does he stand behind what he says, given his own reputation?

If these four elements are present, they can be found at any point in the AI writing process.

But if these elements are absent, the fact that a text is 100% human-written doesn't automatically make it valuable.

Therefore, for brands, the new problem is bigger than just the question of "Should we disclose that we use AI?"

Brands need to ask themselves this question:

What is the source of what we are saying?

Our own customer data?

Is this a real employee experience?

Our area of expertise?

Is this something we've learned from our products?

Or is it simply a more coherent version of ideas already expressed online?

The trust issue created by deepfake technology in the influencer world shows a more extreme version of this. In examples reported by The Guardian, the faces and voices of content creators are being used in advertisements without their knowledge. In such a world, the problem is no longer just "Is this content high quality?" It becomes a more fundamental question: Did this person really say this?

Therefore, in my opinion, the strong brands and thought leaders of the coming period will not be those who shy away from AI.

Those who can use AI better than everyone else will also be able to make their own unique qualities visible.

A real case.

Real data.

A real observation.

A real failure.

True opinion.

A genuine "I see it differently because..." statement.

Their value will increase.

Because production capacity is no longer a differentiating factor.

A few years ago, being able to produce three high-quality articles a week was a capability in itself.

Today, many more people can do this.

Everyone will be able to do it tomorrow.

Therefore, the competition will move beyond a race of "who produces more content?"

Who has more ideas worth mentioning?

The question will be addressed.

This is changing the way I work as well.

I don't see AI as a technology that should be used less. On the contrary, I think we will use it more.

In the research.

In generating counter-arguments.

Think about it in a stress test.

In rapidly prototyping ideas.

In relating different types of data.

But as AI's production capacity grows, I think the human role will shift from production to selection and judgment .

Which idea is truly important?

Which one just looks good?

Which data do I trust?

Where do I disagree with the mainstream?

Which sentence am I willing to publish under my own name?

These questions will become even more valuable, not less, in the age of AI.

Because there's already enough content in the world.

Probably much more than we need.

Something else is missing.

Perspectives we can trust.

Therefore, I would summarize the future of the content economy with a single paradox:

AI will make content cheaper. It will make human reasoning more expensive.

And instead of telling executives, experts, and brands who want to engage in thought leadership to "produce more content," I would ask them a different question:

Which of your thoughts couldn't AI generate by experiencing it for you?