- Some companies are now creating content for two audiences: people and AI systems.
- Comparison pages, listicles and brand mentions are becoming part of the race to appear in chatbot recommendations.
Companies are no longer writing only for human readers.
Some are now creating a second layer of content designed for AI systems.
A report published by The Atlantic highlights how brands are publishing comparison pages, rankings and recommendation-style content that may help them appear in answers from ChatGPT, Gemini, Claude and other AI search systems.
The idea is simple: if AI assistants use public pages as sources, companies have an incentive to publish the kind of pages those systems might cite.
That creates a new version of search optimization. One page may still be written for buyers. Another may be written mainly to influence the machine that recommends what buyers see.
Shopify shows how the tactic works
Shopify is one of the clearest examples in the report.
The company has published at least 60 ranked listicles about e-commerce platforms, according to The Atlantic. The titles vary, but the pattern is similar: Shopify repeatedly appears as the top recommendation in its own comparison articles.
That is not unusual on its own. Companies have always published content that presents their products in a favorable light.
What makes the example more important is how AI systems may use that content.
In one example cited in the report, ChatGPT recommended Shopify as an option for building an online store and included Shopify’s own comparison content among the supporting sources.
Human readers can usually tell when a company ranks itself first. The open question is whether AI systems make that distinction clearly enough.
From SEO rankings to AI recommendations
Traditional SEO focused on ranking in Google.
AI search changes the goal.
Users increasingly receive a single answer, a short list of recommendations or a few cited sources. That means brands are no longer competing only for clicks. They are competing to be included in the answer itself.
That also creates a measurement problem for marketers, because AI-generated answers do not behave like stable search rankings. We recently covered why AI search visibility tools still struggle to measure this new layer of discovery.
The Atlantic identified similar practices among software companies including Figma and ClickUp, which also publish comparison-style content featuring their own products.
Reddit becomes part of the strategy
The report also points to Reddit as an increasingly important source in AI-generated answers.
Because chatbots often cite Reddit discussions, marketers are paying closer attention to how brands are mentioned across relevant communities.
Some SEO practitioners believe those mentions may influence whether a company appears in AI-generated recommendations. The extent of that influence remains unclear, but the direction is obvious: marketers are testing which signals matter in AI search.
The risk: it works until it does not
The short-term incentive is clear. If AI systems pull from comparison pages, listicles and brand mentions, companies will create more of them.
But that does not mean the strategy is safe long term.
In a recent analysis, SEO consultant Lily Ray warned that scaled AI-content strategies can produce early gains before later declines, especially when they rely on repeatable templates rather than durable trust.
What this changes for content strategy
The practical shift is that one piece of content may no longer serve every purpose.
A human-facing page still needs an argument, a point of view and enough detail to be useful. But an AI-facing page is built differently. It needs clean entities, clear comparisons, repeated context, sourceable claims and simple language that can be extracted without much interpretation.
That is why comparison pages, ranked lists and direct alternatives pages are becoming more attractive. They package a brand, category, competitors and recommendation language in a format that AI systems can reuse.
