this post was submitted on 16 Aug 2025
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ChatGPT has some very impressive usage numbers, but the image tells on itself by being a free app. The conversion rate (percentage of people who start paying) is absolutely piss poor, with the very same Ed Zitron estimating it being at ~3% with 500.000.000 users. That also doesn't bode well with the fact that OpenAI still loses money even on their $200/month subscribers. People use ChatGPT because it's been spammed down their throats by the media that never question the sacred words of the executives (snake oil salesmen) that utter lunatic phrases like "AGI by 2025" (Such a quote exists somewhere, but I don't remember if this year was used). People also use ChatGPT because it's free and it's hard to say no to get someone to do your homework for you for free.
I wouldn't really trust Ed Zitron's math analysis when he gets a very simple thing like "there is no real AI adoption" plainly wrong. The financials of OpenAI and other AI-heavy companies are murky, but most tech startups run at a loss for a long time before they either turn a profit or get acquired. It took Uber over a decade to stop losing money every quarter.
OpenAI keeps getting more funding capital because (A) venture capital guys are pretty dumb, and (B) they can easily ramp up advertisements once the free money runs out. Microsoft has already experimented with ads and sponsored products in chatbot messages, ChatGPT will probably do something like that.
Except he doesn't say that. the author of this article simply made that up.
There is a high usage rate (almost entirely ChatGPT btw, despite all the money sunk into AI by others like Google) but its all the free stuff and they are losing bucketloads of money at a rate that is rapidly accelerating.
There is no path to profitability.
I wrote the article, Ed said that in the linked blog post: "There Is No Real AI Adoption, Nor Is There Any Significant Revenue - As I wrote earlier in the year, there is really no significant adoption of generative AI services or products."
There is a pretty clear path to profitability, or at least much lower losses. A lot more phones, tablets, computers, etc now have GPUs or other hardware optimized for running small LLMs/SLMs, and both the large and small LLMs/SLMs are becoming more efficient. With both of those those happening, a lot of the current uses for AI will move to on-device processing (this is already a thing with Apple Intelligence and Gemini Nano), and the tasks that still need a cloud server will be more efficient and consume less power.
I agree that this was poor wording on Ed's side. He meant to point at the lack of adoption for work/business purposes, but failed to articulate this distinction. He is talking about conversion to paid users and how Google cheated to make the adoption of Gemini by corporate users to looks higher than it is. He never meant to talk about the adoption by regular people on the free tier just doing random non-work-related things.
You were talking about a different adoption metric. You are both right, you are just talking about different kinds of adoption.
Oh, when will I get my free phone to do this ?
How exactly will that make OpenAI and the likes more profitable?! That should be one of the scenarios that will make them less profitable.
If the models are more efficient, the tasks that still need a server will get the same result at a lower cost. OpenAI can also pivot to building more local models and license them to device makers, if it wants.
The finances of big tech companies isn't really relevant anyway, except to point out that Ed Zitron's arguments are not based in reality. Whether or not investors are getting stiffed, the bad outcomes of AI would still be bad, and the good outcomes would still be good.