Illustration: AI currently in “good to the users” stage, faces pressure to recoup capital
AI currently in “good to the users” stage, faces pressure to recoup capital
AI feels like it’s standing at a fork in the road. “Right now, I’d say AI is in what Doctorow calls the ‘good to the users’ stage,” one analyst says, noting that many services still seem more focused on what they can actually do for people than on squeezing every last cent out of them. At the same time, the same voice adds a note of worry: “the pressure to make back the massive capital investments will be tremendous, especially for companies whose user base is locked in.” Those locked-in users, Doctorow points out, create a situation where “companies can abuse their users and business…,” a slip that hints at the so-called “Enshittification Trap.” Why should we care?
Because the push-and-pull between giving value and recouping money could end up reshaping how AI tools talk to us. The tech itself is still pretty impressive, but the money behind it might soon tilt design toward revenue grabs rather than user benefit. The real question is whether the industry can dodge that trap before it becomes the default.
Right now, I’d say AI is in what Doctorow calls the “good to the users” stage. But the pressure to make back the massive capital investments will be tremendous—especially for companies whose user base is locked in. Those conditions, as Doctorow writes, allow companies to abuse their users and business customers “to claw back all the value for themselves.” When one imagines the enshittification of AI, the first thing that comes to mind is advertising.
The nightmare is that AI models will make recommendations based on which companies have paid for placement. That’s not happening now, but AI firms are actively exploring the ad space. In a recent interview, OpenAI CEO Sam Altman said, “I believe there probably is some cool ad product we can do that is a net win to the user and a sort of positive to our relationship with the user.” Meanwhile, OpenAI just announced a deal with Walmart so the retailer’s customers can shop inside the ChatGPT app.
Our recent trip to Italy showed AI can already feel useful. A GPT-5 tip steered us to a tiny restaurant on Via Margutta, and the model kept its reasoning hidden, maybe to save the trick for later. Doctorow’s “good to the users” label fits that brief moment when the service lines up with what we want.
Still, the article flags a snag: the massive money flowing into the sector could push things the other way. Companies with big user bases will likely try to squeeze more value out, and the same lock-in that makes the product convenient might also open the door to abuse. It’s hard to say if business models will drift toward practices that hurt users; the pressure to recoup investment is real, but the road ahead isn’t set in stone.
I expect the tug-of-war between short-term perks and longer-term monetisation will shape the next AI wave. We should watch whether firms stay “good to the users” or start leaning toward more self-servicing behavior.
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Common Questions Answered
What does Doctorow's 'good to the users' stage of AI refer to?
The 'good to the users' stage describes a current period where AI services prioritize functionality and user experience over profit extraction. This creates a momentary alignment between the service provided and the user's needs, as exemplified by useful AI suggestions like the GPT-5 recommendation for a memorable dinner.
Why does the article suggest companies with a locked-in user base face pressure?
Companies with a locked-in user base face tremendous pressure to recoup the massive capital investments made in AI development. This lock-in creates conditions where companies have a strong incentive to extract value, potentially leading to the abuse of users to claw back value for themselves.
How does the Italian trip example illustrate the 'good to the users' stage?
The Italian trip example, where a GPT-5 suggestion led to a memorable dinner on Via Margutta, demonstrates AI's current usefulness and alignment with user experience. The model's reasoning remained hidden, which the article suggests might be a tactic to preserve future access and maintain this positive stage.
What is the 'enshittification of AI' that the article warns about?
The 'enshittification of AI' refers to the potential degradation of AI services as companies shift from prioritizing users to extracting profit. The article specifically mentions advertising as a nightmare scenario where this process could begin, driven by the pressure to make back capital investments.