The future of GEO
AI agents that browse and buy on the user's behalf, emerging standards like llms.txt: what current signals suggest, without overstating certainty.
No one can predict with certainty exactly how GEO will evolve, but several current signals point in a reasonable direction: the rise of AI agents acting on the user's behalf, and a likely gradual structuring of technical standards dedicated to AI crawlers. This module is deliberately cautious: the goal is to anticipate trends, not to predict a fixed future.
From answers to actions: the rise of AI agents
So far, most interactions with generative AIs are limited to a question followed by a text answer. Several signals suggest this is shifting toward agents capable of acting directly: browsing a site, comparing offers, filling out a form, even completing a purchase on the user's behalf. Recent announcements around browsing and automated-purchase agents from several model providers point in this direction, though their large-scale adoption remains to be confirmed.
If this trend is confirmed, being visible in an answer won't be enough on its own: the site will also need to be usable by an agent, with clear pages, structured product information, and a purchase flow that doesn't depend on complex interactions designed only for a human. This is a logical extension of what AI share of voice already measures: being present isn't enough, you also need to be usable.
Toward a structuring of technical standards
The llms.txt file, inspired by robots.txt, offers a standardized way to signal to generative AIs which pages to prioritize when understanding a site. Its adoption remains partial today, and its actual impact on visibility results isn't yet clearly established by large-scale independent data. It's reasonable to set it up as a precaution, at low cost, without expecting a guaranteed short-term effect.
More broadly, it's likely that the coming months will see more technical conventions emerge for AI crawlers, similar to what happened for classic SEO with the XML sitemap or schema.org structured data. Nothing indicates, however, that a single standard will quickly dominate; several approaches will probably coexist for a while.
A probable consolidation around sources deemed reliable
Generative AIs appear to be continuously refining their criteria for selecting cited sources, with a growing preference for content that's verifiable, recent, and clearly attributable to an origin. If this trend continues, it would strengthen the advantage of brands that publish original, documented data over those that simply rephrase content already available elsewhere. This is consistent with what's already recommended in the lesson on mistakes that kill your progress: favor precision and original data over volume.
Staying critical of the announcements
GEO attracts a lot of announcements and promotional talk, often phrased in the certain future tense rather than the conditional. A new tool, a new model feature, an article declaring the end of classic SEO: this kind of communication has an incentive to dramatize, which doesn't mean the underlying analysis is wrong, but that it deserves checking before you act on it.
Good practice means distinguishing a change confirmed by observable behavior in your own data from an announcement that, for now, remains an intention or a feature in limited testing. A visibility score that genuinely moves over several weeks after an announced change is a more reliable signal than an article promising a coming revolution.
What probably won't change
Despite these developments, some GEO fundamentals have little reason to disappear. A site's authority, measured through its off-site signals (backlinks, mentions, reputation), will most likely keep playing a role, because it reflects a trust that goes beyond a single page's content. Similarly, the need to answer a question precisely rather than produce generic content will probably remain a central criterion, regardless of how the engines evolve technically.
Without rushing, a few adjustments have a low cost and a defensible upside even if the trends discussed above only partly play out: making product pages more explicit and easier for an automated system to interpret, clearly documenting essential information (price, availability, specifications) rather than scattering it across complex visuals or scripts, and following the evolution of technical standards without rushing to adopt each one the moment it's published.
These adjustments largely overlap with the good practices already recommended throughout this module: precise content, clean technical structure, regular measurement. There's no need for a separate action plan to prepare for the future of GEO — the discipline already in place is enough to absorb most of what's coming.
If a bigger shift does materialize, such as agents completing a significant share of purchases on a user's behalf, it will most likely show up gradually in your own data before it becomes obvious in the trade press: a slow rise in sessions with unusual navigation patterns, a growing share of traffic from sources you can't fully attribute yet. Keeping an eye on these edge cases in your analytics, without over-interpreting a handful of sessions, is a reasonable way to stay ahead without acting on speculation alone.
How to position yourself without over-investing in uncertain bets
The right posture in the face of this uncertainty isn't inaction, but proportionality: put in place the low-cost, reversible adjustments now (technical structuring, llms.txt, factual and sourced content), and stay alert to signals that would confirm or contradict the bigger trends, like a real rise in transactional agents. Regular tracking of the KPIs that matter is exactly the tool that lets you catch these shifts early, without having to bet today on one scenario over another.
GEO will likely remain, in the months ahead, a field that moves faster than classic SEO did in its early days. The discipline of continuous measurement and adjustment built throughout this module is what lets you keep pace without having to rebuild everything at every change.