Information gain is a simple but important SEO idea.
It means your article should add something useful that is not already found in the same old results.
That might be first-hand experience, original photos, your own testing, a better explanation, a different angle, or a practical example that comes from real life.
But here is the problem.
Even advice about information gain can become generic.
To test this, I asked two AI tools the same basic question:
“Give me four ways an article can generate information gain for SEO purposes.”
I asked Google AI Mode.
I also asked ChatGPT.
Here is what happened.
| Google AI Mode | ChatGPT | Similar idea? |
|---|---|---|
| First-Hand Experience | First-Hand Experience | Yes — almost identical |
| Original Visuals | Specific detail / first-hand evidence | Similar — both are about adding proof or originality |
| Data and Experiments | Original Testing or Comparison | Yes — very similar |
| Contrarian Perspectives | Better Framework or Specific Insight | Similar — both are about adding a different angle |
The answers were not exactly the same.
But they were close enough to make the point.
If 100 website owners ask AI to write an article about information gain, many of them will probably get similar advice.
They will be told to add experience.
They will be told to add original images.
They will be told to run tests.
They will be told to offer a different perspective.
That advice is useful.
But if everyone publishes the same advice, in the same structure, with the same examples, the content quickly becomes part of the same generic middle ground.
And that is exactly the problem information gain is trying to solve.
The Real Lesson
The information gain in this article is not simply saying:
“Use first-hand experience, visuals, data, and contrarian opinions.”
That list already exists.
The useful part is the small live experiment.
I asked two different AI systems the same question.
I compared the answers.
I noticed how similar they were.
And that helped me understand the issue more clearly.
Information gain is not just about knowing the theory.
It is about adding something that came from your own process, your own test, your own mistake, your own comparison, or your own experience.
That is the difference.
A generic AI article might say:
“Add original research to your content.”
A more useful article says:
“I tested this myself, here is what I found, and here is what it taught me.”
Why This Matters for Website Owners
AI can produce decent articles very quickly.
But that is also the danger.
If everyone uses AI to ask the same questions, they will often get similar answers.
Those answers may be accurate.
They may be well written.
They may even be helpful at a basic level.
But they may not add anything new.
That is why simply generating articles is not enough.
You need to bring something to the process.
A test.
A comparison.
A real example.
A photo.
A mistake.
A practical result.
A personal observation.
In this case, the article became stronger because it did not just explain information gain.
It demonstrated it.
That is the key point.
Information gain is not created by saying something should be original.
It is created by doing something original enough that the article could only have come from you.