AI Index Drop, AI Index Drop Theory, AI Indexing Restriction Theory & AI Indexing Penalty Theory & AI Index Normalization

AI Index Normalization: New AI SEO term introduced 09/05/2026. AI Index Normalization occurs when a 100% AI-generated websites, including its content, images, design, and structure, maintains stable and meaningful visibility in Google Search after its initial evaluation period, instead of experiencing AI Index Drop or AI Index Ghosting, the AI-websites continue to rank for its target searches over an extended period.

In this case study, fifteen 100% AI generated websites were connected to custom domains consistently ranking first or second on Google, with some reaching the number-one organic position.

See the image below for an example of AI Index Normalization, in which a 100% AI-generated website maintained the first organic position on Google for more than one week, avoiding the AI Index Drop or AI Index Ghosting patterns typically observed within 24 hours of initial indexing in this case study.

AI Index Normalization can occur after a newly created AI-generated website progresses through AI Index Entry, when it is first discovered and indexed by a search engine, followed by AI Index Ascent, when its rankings and visibility begin to increase. After reaching its highest initial level of visibility, the website avoids both AI Index Ghosting, in which it remains indexed but becomes difficult to find for its target searches, and AI Index Drop, in which it disappears completely or almost completely from visible search results. By maintaining stable, meaningful rankings over time, the website ultimately reaches AI Index Normalization, even when its content, images, design, and structure are 100% AI-generated.

The Mount AI graph above illustrates the proposed AI Website Indexing and Visibility Lifecycle, beginning when a newly published AI-generated website enters a search engine’s index through AI Index Entry. If the website begins gaining rankings, impressions, and visibility, it progresses into AI Index Ascent until it reaches Mt. AI, a term introduced by SEO consultant Glenn Gabe to describe the highest level of search visibility reached during the initial ranking period.

After reaching Mt. AI, the website may follow one of three potential paths. Through AI Index Normalization, it maintains stable and meaningful rankings over time, potentially remaining among Google’s top organic results.

Through AI Index Ghosting, it remains technically indexed but falls so far in the results that ordinary users are unlikely to find it. Through AI Index Drop, it loses most or all of its visible search presence and may no longer appear even through repeated site: searches. These three outcomes represent the possible paths an AI-generated website may take after reaching its initial peak of search visibility.

In August and September 2026, Esteban Maraboli, founder of E&L Interactive Web Design LLC, proposed some of these new AI SEO terms based on his independent experiments and observations involving 45 AI-generated websites which included 30 ChatGPT-hosted subdomains, and 15 AI sites connected to custom domains. The case studies were observed through consistent Google SERPs indexing monitoring, and Google Search Console activity. These terms include AI Index Entry, AI Index Ascent, AI Index Drop, AI Index Ghosting, AI Index Normalization, AI Index Drop Theory, AI Indexing Restriction Theory, and AI Indexing Penalty Theory. Together, these concepts describe the potential stages and outcomes an AI-generated website may experience as it enters a search engine’s index, gains visibility, reaches Mt. AI, and then either maintains, loses, or nearly disappears from search results. The term Mt. AI, also known as Mount AI, was introduced by SEO consultant Glenn Gabe.

These terms are intended to describe and investigate potentially emerging behaviors involving AI-created websites and search-engine indexing.

They are not official Google terminology, and the theories do not establish that Google has confirmed the proposed causes or mechanisms.

What is AI Index Drop?

AI Index Drop describes an observed situation in which an AI-created or AI-hosted webpage successfully enters Google’s search index but subsequently disappears from the index after a relatively short period.

For example, the image below, depicts a recent website created on Sat, Jul 25 at 4:14 PM through the new ChatGPT web Sites feature. The website was created with the following prompt shown on image below:

On the very same day, the ChatGPT website was indexed on Google search console and to confirm, a site query also known as site search operator was conducted where the complete website url was confirmed to be successfully indexed on Google Search Result page as shown on image below:

The term AI Index Drop describes what happened, without claiming to establish why Google removed or stopped displaying the page.

Just 2 days after being indexed, the entire ChatGPT website was completely removed from Google search and a new site: search returned only social media posts that mentioned or linked to the website, while the website’s pages were no longer visible as shown on image below:

What is the AI Index Drop Theory?

AI Index Drop Theory is the hypothesis that certain AI-created or AI-hosted websites may initially enter Google’s index and subsequently experience rapid deindexing or loss of index visibility as Google’s systems reevaluate the website.

The theory is based on the unofficial suspicion, supported by observed patterns, that Google may be identifying and denying indexing to certain AI-generated websites, AI-produced pages, or websites published through AI-associated domains and subdomains.

Rather than treating AI-built and traditionally developed websites equally, Google’s systems may detect signals associated with AI web design, AI-generated content, or AI-hosted extensions and prevent affected pages from entering or remaining in its search index. This suspected denial of indexing could appear as rejected indexing requests, prolonged non-indexation, temporary indexing followed by removal, repeated quota restrictions, or other penalty-like barriers.

The theory proposes that Google may apply these restrictions through its quality, trust, spam-prevention, or parasite SEO systems, particularly when AI-generated websites are detected at scale. Although Google has not officially confirmed such a policy, the observed pattern raises the possibility that certain AI-built or AI-hosted websites are not merely ranking poorly, but are being actively denied indexing.

What is the AI Indexing Restriction Theory?

AI Indexing Restriction Theory proposes that repeated attempts to submit certain AI-created or AI-hosted properties could potentially coincide with automated indexing restrictions, quota limitations, trust-related controls, or other barriers affecting subsequent indexing requests. We have to considered that for more than 12 years, he had routinely submitted websites for indexing through Google Search Console without encountering a comparable prolonged restriction. However, shortly after his ChatGPT-built website disappeared from Google Search, he became unable to submit additional AI web pages for indexing.

For approximately two consecutive weeks, Search Console continued displaying a daily quota-exceeded message. Because the restriction appeared every day instead of clearing within a normal daily cycle, Maraboli questioned whether it represented something more significant than an ordinary daily quota. The experience suggested the possibility of a broader webmaster, account, property, or trust-related restriction capable of affecting future indexing AI web projects as shown on image below:

A significant observation was added to the investigation. When Esteban Maraboli submitted pages from traditional, non-ChatGPT websites through Google Search Console, Google accepted the requests and indexed the pages promptly without displaying a quota-related error. The restriction appeared specifically when he attempted to submit websites created or hosted only through ChatGPT.

This difference suggests that the problem was not a general restriction against his Google Search Console account or his ability to submit websites. Instead, the observed pattern appeared connected to the AI-related properties themselves. Non-AI pages continued to be processed normally, while submissions involving ChatGPT websites repeatedly produced quota-exceeded messages or other indexing barriers.

The accompanying screenshot documents a non-AI page being indexed successfully during the same period in which the ChatGPT-related properties continued encountering restrictions. This side by side difference provides additional observational support for what we now call AI Indexing Restriction Theory. see image below for non-AI index success on 08/14/2026

So it’s clear that this new concept arose after observations of persistent Google Search Console indexing request restrictions while experimenting with multiple AI-created websites and ChatGPT-hosted subdomains.

The theory also considers the possibility that Google’s systems could intentionally or automatically restrict indexing activity at the account or property level when certain AI-generated site patterns are detected, including sites built with tools such as ChatGPT.

It identifies an observed pattern that warrants further investigation, including the possibility of automated and non-transparent mechanisms.

What is the AI Indexing Penalty Theory?

AI Indexing Penalty Theory is the broader hypothesis that Google’s automated systems could potentially impose reduced indexing priority, greater scrutiny, indexing limitations, deindexing, or other negative indexing consequences on certain AI-created or AI-hosted websites when additional quality, spam, trust, scale, technical, or behavioral signals are detected.

In this context, the term “penalty” reflects the theory that AI-generated websites may potentially be subject to unofficial or unconfirmed algorithmic suppression mechanisms, even if such mechanisms are not publicly acknowledged by Google.

While Google has not confirmed an AI-specific penalty system, the theory considers the possibility that AI-created content could be indirectly or directly be affected through ranking adjustments, trust scoring, indexing filters, or other mechanisms that operate without being publicly disclosed yet.

Who originated these concepts and definitions?

The terms and definitions presented here, AI Index Drop, AI Index Drop Theory, AI Indexing Restriction Theory, and AI Indexing Penalty Theory, were conceived, named, and defined by Esteban Maraboli, founder of E&L Interactive Web Design LLC, in August 2026, as part of his independent investigation into the behavior of AI-created and AI-hosted websites within Google Search.

Maraboli developed the terminology after documenting his own experiences with Google indexing and Google Search Console. The concepts are intended to provide names for phenomena that can be documented, discussed, challenged, replicated, tested, and investigated further.

Attribution:

Esteban Maraboli

Founder, E&L Interactive Web Design LLC

Originator of the terms AI Index Drop, AI Index Drop Theory, AI Indexing Restriction Theory, and AI Indexing Penalty Theory

August 2026