OpenAI is about to repeat Google’s Gemini 3 mistake

OpenAI is about to play follow the leader…over a cliff. The leader is Google. The cliff is trust.

By embedding Google’s Gemini directly into the Chrome browser, Google bet that exposure will fix AI’s stalled adoption. That if Gemini 3 is everywhere, users will finally embrace it.

They won’t.

Adoption didn’t stall because users couldn’t find Gemini.

It stalled because users didn’t trust what they found.

Now OpenAI is making a different mistake — driven by the same misunderstanding

Unlike Google, OpenAI doesn’t have a distribution problem. ChatGPT already sits at the center of the AI conversation. Users didn’t need a browser button to find it.

What OpenAI has is a revenue problem.

According to Menlo Ventures, “ChatGPT, with its first-mover advantage, only converts about 5% of its weekly active users into paying subscribers — a strikingly low conversion rate and one of the largest and fastest-emerging monetization gaps in recent consumer tech history.”

Despite massive usage, only a small fraction of users pay for subscriptions. The overwhelming majority use ChatGPT for free. And the economics are unforgiving:

• Inference is expensive.
• Compute costs scale with usage.
• And “free” users generate the bulk of that cost.

Subscriptions alone don’t close the gap.

That is the quiet pressure behind OpenAI’s recent signaling around advertising — not innovation, not strategy, but arithmetic.

When a company with enormous demand still can’t make the numbers work, it starts looking for revenue it can graft onto the product it already has.

That’s where ads come in.

Why advertising inside ChatGPT is a structural error, not a product tweak

Advertising is not neutral when inserted into a reasoning system.

Search engines can survive ads because users see many results. They compare. They judge. They understand ranking as inherently commercial.

A conversational AI does not work that way.

ChatGPT presents a single, authoritative answer — written in fluent, confident prose. When advertising influences that answer, the user loses the ability to tell:

• whether a recommendation is true or paid
• whether confidence reflects certainty or sponsorship
• whether the system is reasoning or persuading

Disclosures do not fix this.

A small “sponsored” label cannot restore the answer the user never sees — the unsponsored version that no longer exists.

Once users suspect that responses are optimized for monetization rather than accuracy, the product crosses a line it cannot uncross.

Trust doesn’t degrade gradually in systems like this.
It collapses.

Advertising directly attacks the one asset ChatGPT still has

OpenAI itself regularly invokes the phrase “trusted relationship with users.” That trust is the entire product.

Users ask ChatGPT things they would not ask a search engine:

• how to frame legal arguments
• how to interpret medical information
• how to make financial decisions
• how to evaluate tradeoffs

The moment users believe that answers may be shaped by advertisers, every one of those interactions becomes suspect.

And unlike social media, there is no “casual mode” here.

ChatGPT does not live on vibes.
It lives on credibility.

Once that credibility is compromised, users don’t stick around to “see how bad it gets.” They quietly leave — exactly the pattern already visible in stalled adoption data.

The irony OpenAI appears to be missing

Google tried to fix a credibility failure with distribution.

OpenAI now appears ready to fix a revenue failure with influence.

Both mistakes come from the same false premise: that adoption stalls because AI isn’t visible enough or monetized cleverly enough.

In reality, adoption stalls when users stop believing the system.

Advertising doesn’t rebuild belief.
It accelerates doubt.

The deeper problem ads cannot solve

Even if advertising worked perfectly — which it won’t — it still would not address the core issues holding AI back:

• lack of memory
• lack of uncertainty signaling
• lack of user-governed control
• lack of alignment between cost, value, and pricing

Ads are a workaround for not having a real revenue model.
They are not a foundation.

And when ads collide with trust in a reasoning system, trust always loses.

The lesson Google already demonstrated

You cannot force adoption by pushing AI into more surfaces.
And you cannot fund AI by quietly selling influence inside answers.

AI succeeds only when users believe it is trying to be right — not persuasive, not optimized, not monetized.

Google ignored that lesson with Gemini.

OpenAI has a chance to avoid repeating it.

If it doesn’t, the outcome will look familiar:
initial curiosity > skepticism > abandonment

Not because AI isn’t powerful.

But because it stopped being believable.