Google's Gary Illyes said bot impersonation has become more of an issue with AI. For anyone who manages a website, that short statement points to a growing headache: it is becoming harder to tell which automated visitors are who they claim to be. When bots present as other bots or as legitimate crawlers, log files, crawl management, and security decisions all become less reliable, and the work of running a site gets more complicated.
In general terms, bot impersonation means a bot presenting itself as something it is not. The most common form is a bot claiming to be another bot, or claiming to be a legitimate crawler, when it is in fact a different system with different purposes. A visitor that says it is a well-known search crawler may not be that crawler at all, and a visitor that claims an AI identity may be something else entirely.
Impersonation works because much of the web's bot handling relies on self-identification. A bot announces itself, usually through a user agent string, and the site decides how to treat it based on that announcement. That system works when bots are honest about who they are. It breaks down when they are not, because the site's decision is then based on a false premise.
Log analysis is the first place impersonation causes trouble. Logs record which visitors came, what they requested, and how often, and site owners use those records to understand crawl behavior, diagnose problems, and plan capacity. If some of those visitors are misidentified, the conclusions drawn from the logs will be wrong in ways that are hard to spot.
A spike in requests attributed to a legitimate crawler, for example, might actually be a different bot wearing that crawler's name. A team that trusts the label will investigate the wrong system, adjust the wrong settings, or draw the wrong conclusion about how their site is being crawled. The log is only as trustworthy as the identities in it.
Crawl management depends on the same identities. Site owners use tools such as robots files and crawl controls to guide legitimate crawlers, limit wasteful crawling, and protect server resources. Those controls work by naming the bots they apply to, and they assume the bots will respect the names they are given.
Impersonation undermines that assumption from both directions. A bot that impersonates a legitimate crawler may bypass limits intended for other bots, consuming resources that were meant to be reserved. A bot that impersonates a different system may be blocked or allowed based on a mistaken identity, producing crawl behavior that looks erratic even though the rules themselves are sound.
Security is the third area affected, and the most consequential. Bots that can pass as legitimate crawlers may gain a level of trust that lets them probe a site more freely, collect more data, or find weaknesses that would otherwise be harder to reach. A crawler identity is, in effect, a claim to be a welcome guest, and a false claim can open doors that should have stayed closed.
That risk is not limited to dramatic attacks. Even routine data collection becomes a security concern when it is done under a false identity, because the site owner cannot accurately assess who has their content, how much of it they took, or what they intend to do with it. Visibility into who is accessing a site is a basic security requirement, and impersonation removes it.
For security teams, the implication is that bot identity needs to be treated as a security question, not just a traffic question. The question is not only how much traffic a bot generates, but whether the bot is who it says it is, and what access that claim has granted it.
Illyes's statement does not come with a set of remedies attributed to Google in the report, and this article does not invent any. What it offers is a diagnosis: bot impersonation has become more of an issue with AI, and site owners should expect bot identity to be less reliable than it once was.
The practical stance that follows from that diagnosis is caution. Treat bot labels in logs as claims to be checked, not facts to be filed. Review crawl patterns for inconsistencies that might suggest misidentification. And keep security decisions grounded in verification, not in a visitor's self-declared name.
Source: Search Engine Roundtable, October 30, 2026.
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