I tried a small live search experiment today, and it helped me think more clearly about the difference between commodity content and genuinely helpful content.
The search was very simple.
I Googled:
How to repair a corroded battery compartment
Google returned an AI Overview explaining the basic process. In summary, the AI answer said that to fix a corroded battery compartment, you should remove the old batteries, neutralise the corrosion with white vinegar or lemon juice, scrub the metal contacts clean, wipe the area with isopropyl alcohol, allow it to dry, and then apply a very thin layer of petroleum jelly to help prevent future corrosion.
The AI Overview then broke the process down into steps:
- Safety first
Wear safety glasses and rubber gloves, switch the device off, and remove the leaking batteries. - Neutralise the corrosion
Use white vinegar or lemon juice on a cotton swab or toothbrush and apply it to the corroded terminals. - Scrub and scrape
Use a toothbrush, small screwdriver, emery board, or brass brush to remove stubborn corrosion. - Clean and dry
Wipe the terminals with isopropyl alcohol, dry the area, and leave the compartment open before adding new batteries. - Prevent future buildup
Apply a very thin layer of petroleum jelly to the metal contacts.
The AI Overview also showed supporting resources, including a YouTube video demonstration, an Instructables result, Reddit discussion, and other pages about cleaning battery corrosion.
That was the interesting part for me.
The AI answer was useful. It gave the basic steps clearly. But as I looked at it, I realised that this is exactly what commodity content now looks like.
The basic answer is available instantly.
So the question for a website owner is not:
“Can I write an article that says the same thing?”
The better question is:
“What would a real person still need after reading this?”
That is where the opportunity starts.
The AI Overview Gave the Steps, But Not the Full Pathway
The AI Overview told me to neutralise the corrosion.
But if I were actually repairing a battery compartment, I might still be wondering:
How much vinegar should I use?
Should the cotton swab be damp or wet?
What if the liquid runs into the device?
How much fizzing is normal?
What if there is no fizzing at all?
Should I scrape hard or gently?
What if the spring is fragile?
What if the corrosion has eaten through the metal?
What if the device still does not work afterwards?
Should I keep trying, or is the device beyond repair?
These are the kinds of questions that often appear once someone moves from reading an answer to actually doing the task.
That is the important distinction.
AI can often provide the recipe.
But a genuinely helpful website can provide the pathway.
The Video Result Was Also Interesting
Another thing I noticed was that the AI Overview did not only give written steps. It also included a video result for a visual demonstration.
That made me think about how Google may be trying to match resources to different parts of the task.
For a practical repair job, a written guide may not be enough. People may want to see what the corrosion looks like, how much pressure to use, what tool to use, and what a cleaned terminal should look like afterwards.
So rather than only creating one broad article called:
How to Clean Battery Corrosion
there may be an opportunity to create more specific supporting content, such as:
How to Clean a Corroded Battery Spring Without Breaking It
What Battery Corrosion Looks Like Before and After Cleaning
How Much Vinegar Should You Use on Battery Terminals?
How to Tell If a Battery Compartment Is Too Damaged to Repair
Cleaning Battery Corrosion From a Remote Control: Real Example
Those are not just generic answers. They are practical, specific, and useful at the point where someone may be unsure.
This made me think that content opportunities may still exist, but they are becoming more precise.
The broad answer is often covered.
The detailed, confidence-building support is where the human creator can still add value.
How This Turns Commodity Content Into Non-Commodity Content
The commodity version of the article would simply repeat the AI Overview:
Remove the batteries.
Use vinegar.
Scrub the terminals.
Dry the compartment.
Put in new batteries.
That is useful, but it is not especially distinctive.
The non-commodity version would go further.
It would include:
Photos of the actual corroded battery compartment.
A clear warning about not flooding the device with liquid.
A close-up of the tools used.
A real example of a spring contact before and after cleaning.
A note about what worked well and what did not.
A section on common mistakes.
A section on when the device may be too damaged to repair.
A short video showing the process.
A checklist of supplies.
A troubleshooting section for what to do if the device still does not work.
That kind of content feels different.
It is not just repeating known information. It is helping someone complete the job with more confidence.
My Thought Process From This Search
The search experiment led me to a useful content creation method.
First, search for a practical question and look at the AI Overview.
Second, identify the basic steps the AI gives.
Third, ask whether those steps are now commodity information.
Fourth, look for the uncertainty behind each step.
Fifth, build content around those uncertainties.
For the battery corrosion example, the AI says:
“Scrub and scrape the terminals.”
But the real person thinks:
“How hard do I scrape?”
The AI says:
“Use vinegar or lemon juice.”
But the real person thinks:
“Can I damage the electronics if I use too much?”
The AI says:
“Let it dry completely.”
But the real person thinks:
“How long is completely?”
The AI says:
“Apply petroleum jelly.”
But the real person thinks:
“How much is a thin layer, and do I really need to do this?”
Those questions are where better content can be created.
The Bigger Lesson
This live search experiment helped me see the future of helpful content more clearly.
AI Overviews are very good at giving the standard answer.
That means website owners need to think beyond standard answers.
The opportunity is not simply to produce more articles that say what everyone else already says.
The opportunity is to add:
experience,
judgement,
examples,
photos,
videos,
mistakes,
warnings,
comparisons,
testing,
and practical reassurance.
That is what makes content feel human.
In this battery corrosion example, a thin article might be replaced by an AI Overview.
But a genuinely useful guide based on a real repair, with photos, close-ups, warnings, decision points, and troubleshooting, still has value.
The AI Overview can tell someone what to do.
A helpful website can show them how to do it properly, what to watch out for, and how to know whether they are succeeding.
That, to me, is the difference between commodity content and non-commodity content.
And the useful insight from this little experiment is that AI Overviews may not only be a threat.
They can also be used as research tools.
They show us the basic answer.
Then our job is to ask:
“What is missing?”
That missing part is often where the real content opportunity lives.