If You Update Your Website Today, When Will AI Start Using It?

One of the most common questions businesses ask about AI visibility is surprisingly simple:

"If I update my website today, how long until ChatGPT starts recommending me?"

The answer is frustrating.

It depends entirely on which AI platform you're talking about.

Many marketers assume all AI systems work like Google. Update a page, wait for it to be crawled and eventually you'll see the change reflected in search results.

That's not how modern AI platforms work.

Some AI systems actively search the web every time a user asks a question. Others rely heavily on information learned during training. Many use a combination of both.

This means a change you make today could appear in one AI platform within hours while remaining invisible in another for months.

For businesses investing in GEO, understanding this difference is essential.

The biggest misconception in AI search

The phrase "LLM" often creates the impression that all AI systems work in the same way.

In reality, today's leading AI platforms operate very differently when it comes to information retrieval.

Broadly speaking, there are two approaches.

The first relies primarily on training data. The model generates answers based on information it learned before deployment.

The second combines model knowledge with live web retrieval. These systems actively search the internet and incorporate current information into responses.

Most major AI platforms now sit somewhere between these two extremes.

The challenge for marketers is understanding where each platform falls on that spectrum.

Google AI Overviews: usually the fastest

If your goal is rapid visibility, Google AI Overviews are currently among the most responsive AI systems available.

Unlike standalone chatbots, AI Overviews are built directly on top of Google's search infrastructure. Google has confirmed that AI Overviews use a customised Gemini model alongside its existing search systems, ranking infrastructure and web index.

In practical terms, this means AI Overviews can access newly indexed content very quickly.

If Google discovers and indexes a page, there's a realistic chance that information could begin influencing AI Overviews within days and, in some cases, much sooner.

This doesn't mean every content update immediately appears in AI-generated answers. AI Overviews still decide which sources to use and which information is relevant.

However, the underlying data is generally very fresh.

Typical visibility timeframe

New content indexed by Google: hours to days
Potential AI Overview visibility: days to weeks
Full authority impact: weeks to months

Google AI Mode follows a similar model

Google's newer AI Mode takes this even further.

Rather than presenting a static overview above search results, AI Mode is designed as a conversational search experience. It combines Gemini with Google's search systems and retrieves information dynamically as part of the answer generation process.

From a GEO perspective, this means AI Mode behaves much more like a search engine than a traditional LLM.

If your content is visible to Google Search, it can potentially become visible to AI Mode relatively quickly.

The challenge is less about indexing speed and more about whether Google considers your content trustworthy enough to include.

ChatGPT: the answer depends on which version users are using

ChatGPT is where things become more complicated.

Many businesses still assume ChatGPT operates entirely on training data. That was largely true in earlier versions, but it's no longer the full picture.

Today, ChatGPT can search the web and retrieve current information. OpenAI's own documentation confirms that web search allows models to access up-to-date information and cite current sources.

However, not every interaction uses web search.

When web search is not being used, responses may rely heavily on the model's training and internal knowledge. In those situations, recent changes to your website may not be reflected immediately.

This is where many GEO discussions become confusing.

A business might ask ChatGPT about their company and receive one answer. Another user may ask a similar question and trigger web search, producing a completely different response.

Typical visibility timeframe

With web search:

Hours to days

Without web search:

Potentially months until reflected in future model updates

This is one reason monitoring actual AI responses is becoming so important.

Perplexity is designed around live retrieval

Perplexity operates differently from most AI assistants.

The platform was built around search from the beginning and places citations at the centre of the experience. Rather than relying primarily on model memory, Perplexity routinely retrieves information from live web sources before generating responses.

For brands, this means content changes can often appear much faster than they would in a purely training-data-driven system.

If Perplexity can crawl and access your content, visibility can change relatively quickly.

This also means Perplexity tends to reward businesses that publish current, authoritative information on a regular basis.

Typical visibility timeframe

New content discovery: hours to days
Potential citation visibility: days
Authority-building impact: weeks to months

Claude has changed significantly

Historically, Claude relied much more heavily on model knowledge than some competitors.

That has changed.

Anthropic now offers web search capabilities that allow Claude to access current information from across the internet. The company describes web search as a tool that enables Claude to deliver up-to-date insights rather than relying solely on training data.

This means the freshness of Claude's answers increasingly depends on whether web search is being used.

When search is enabled, Claude can retrieve current information and reference recent developments. When it isn't, responses rely more heavily on the underlying model.

Typical visibility timeframe

With web search:

Hours to days

Without web search:

Potentially many months

Grok is built around real-time information

One reason Grok has attracted attention is its access to real-time content.

Because it is deeply integrated into X, Grok is often able to surface and discuss developments very quickly.

For fast-moving topics, this can make Grok one of the most current AI systems available.

The downside is that recency does not always equal authority. Real-time information can be valuable, but it also introduces new challenges around accuracy and source quality.

For brands, however, it means updates can potentially influence responses very quickly.

What about Meta AI and Llama?

Meta's position is slightly different.

Llama itself is a model family rather than a search engine.

Whether a Llama-powered assistant can access current information depends heavily on how that assistant has been implemented. Some versions incorporate live retrieval systems, while others rely primarily on model knowledge.

This means there is no single answer for "Llama visibility".

The timeline depends entirely on the specific application using the model.

So how long does GEO actually take?

The honest answer is that GEO operates on two timelines.

Timeline one: discovery

Can the AI platform see your content?

For search-connected systems such as Google AI Overviews, AI Mode, Perplexity, ChatGPT Search and Claude with web search enabled, the answer may be measured in days.

Timeline two: trust

Does the AI platform consider your content authoritative enough to reference?

This takes much longer.

AI systems evaluate authority through citations, external references, entity signals, brand consistency and overall source quality. Updating a single page today does not automatically make a brand recommendable tomorrow.

For most businesses, meaningful GEO improvements are usually measured in months rather than days.

The real goal isn't indexing

Many marketers approach GEO as if it were SEO.

They focus on getting content discovered.

Discovery matters, but it's only the first step.

The more important question is whether AI systems trust your content enough to use it.

Google AI Overviews, ChatGPT, Perplexity, Claude and other platforms are increasingly acting as editors. They decide which sources deserve visibility and which do not.

That means GEO isn't simply about publishing content.

It's about building authority that AI systems recognise.

The future of AI visibility will be faster

One trend is already clear.

Most major AI platforms are moving towards greater use of real-time information.

OpenAI has web search. Claude has web search. Google's AI experiences are built directly on search infrastructure. Perplexity was designed around live retrieval from day one.

As a result, the delay between publishing information and seeing it reflected in AI responses is shrinking.

The real challenge is no longer how quickly AI can find your content.

It's whether AI considers your content worth recommending in the first place.

And that's ultimately what GEO is trying to solve.

References

OpenAI – Web Search Documentation
https://developers.openai.com/api/docs/guides/tools-web-search

OpenAI – ChatGPT Overview
https://chatgpt.com/overview

Google – How AI Overviews Work
https://static.googleusercontent.com/media/www.google.com/en//search/howsearchworks/google-about-AI-overviews.pdf

Google Support – AI Overviews in Search
https://support.google.com/websearch/answer/14901683

Anthropic – Introducing Web Search on the Anthropic API
https://www.anthropic.com/news/web-search-api

Ars Technica – Anthropic's New AI Search Feature Digs Through the Web for Answers
https://arstechnica.com/ai/2025/03/anthropics-new-ai-search-feature-digs-through-the-web-for-answers/

Measuring Google AI Overviews: Activation, Source Quality, Claim Fidelity, and Publisher Impact
https://arxiv.org/abs/2605.14021