How do you optimise blogs for answer engines?

Blogging has always been shaped by technology, from the early days of basic websites to the rise of search engine optimisation. Now, a new shift is underway. With artificial intelligence tools like ChatGPT and Gemini becoming part of everyday search behaviour, bloggers are asking how their content fits into this changing landscape.

Why are bloggers asking about ChatGPT and Gemini?

Artificial intelligence has changed the way people discover and consume information online. Where Google Search was once the main gateway to blogs, tools like ChatGPT and Gemini are now part of that journey. Instead of typing a query and browsing links, readers can ask AI assistants for instant, conversational answers.

For bloggers, this shift raises an important question: how do these AI tools handle blog content? Do they crawl and index posts like Google does, or do they rely on a completely different process?

This blog explores the differences between ChatGPT and Gemini, how each interacts with written content, and what bloggers can do to ensure their posts are visible and valuable in an AI-driven world.

Wrap-up

In short, the way AI models work with blogs is not the same as traditional SEO. To understand why, we first need to look at what “indexing” really means.

What does “indexing” mean for AI models?

When we talk about search engines like Google, indexing refers to the structured process of crawling, storing, and ranking webpages. ChatGPT and Gemini, however, don’t “index” in this traditional sense. Instead, they rely on training data, APIs, and real-time connectors to process text.

For example, Googlebot crawls a blog post, stores it in an index, and ranks it for relevant keywords. In contrast, ChatGPT uses patterns it learned during training, and Gemini draws on live integration with Google Search to surface insights.

In short, AI models don’t maintain a searchable index of every blog, but they can still understand and summarise content when accessed.

How does ChatGPT handle blog content?

ChatGPT doesn’t actively crawl or store blogs like a search engine. Instead, it processes blog content in three main ways:

1. Training data – Blog posts that were publicly available before its last training cut-off may be included in the model’s knowledge base. This means ChatGPT can sometimes draw on generalised patterns, insights, or language from blogs that existed during training, though it does not retain or “remember” specific documents.

2. Plugins and connectors – Businesses and creators can connect ChatGPT to their own databases, websites, or content management systems. Through these integrations, the AI can access and interpret blog posts directly, making it useful for internal knowledge sharing, content automation, or customer support.

3. User input – The most common method is when a user pastes or uploads a blog post directly into ChatGPT. The model then analyses the content in real time, generating summaries, alternative formats, or creative variations.

Why this matters for bloggers

Unlike Google, which scans the web continuously, ChatGPT only works with what it’s trained on, connected to, or given in the moment. This means that if a blogger wants ChatGPT to “see” their latest article, they must either provide it manually or connect it via a plugin.

Practical examples

• Example 1: A marketing team uploads their latest 1,500-word blog into ChatGPT. Within seconds, the AI generates multiple LinkedIn captions, a tweet thread, and an email subject line, saving hours of manual repurposing.

• Example 2: A lifestyle blogger feeds an old article into ChatGPT and asks it to “rewrite this in a more conversational tone.” The AI restructures the content into shorter paragraphs, suggests modern examples, and creates a fresher version for reposting.

• Example 3: An eCommerce brand connects its knowledge base to ChatGPT. When customers ask product-related questions, ChatGPT can reference relevant blog posts and provide tailored, conversational responses.

Wrap-up

In summary, ChatGPT doesn’t “index” content in the search engine sense. Instead, it reads, interprets, and transforms blog content when it is given directly, integrated via connectors, or included in training. This makes it a powerful tool for content creation and repurposing, but it should not be mistaken for a live crawler or index like Google.

How does Gemini process blog content differently?

Gemini, developed by Google, has a closer relationship with live web data. While it does not index in the traditional SEO sense, it leverages Google Search to pull the latest information.

Key differences include:

• Real-time web awareness – Gemini can access Google’s search index for up-to-date insights.

• Direct integration with Google products – Making it powerful for bloggers already reliant on Google’s ecosystem.

• Contextual responses – It cross-references search data with its model knowledge to give relevant answers.

Example 1: A blogger researching trends can ask Gemini to summarise the top-ranking articles on “AI in blogging” today.
Example 2: A business owner can get live data about competitors’ blog strategies directly through Gemini’s search connections.

Wrap-up

Overall, Gemini is better positioned for fresh content visibility, while ChatGPT is stronger for analysis and rewriting tasks. For bloggers, this means thinking about both freshness and clarity when creating posts.

Can bloggers optimise for AI discovery?

Yes, but not in the same way as SEO for Google. Optimising for AI involves focusing on clarity, structure, and authority rather than just keywords.

Best practices include:

• Writing clear, well-structured blog posts with headings that help AI models summarise content.

• Using natural, conversational language instead of keyword stuffing.

• Publishing authoritative content that other websites may reference, boosting visibility both in Google and indirectly in AI models.

Example 1: A blog with structured FAQs at the end is more likely to be quoted by AI when answering related queries.
Example 2: A business blog with concise summaries in each section improves AI-driven overviews.

Wrap-up

In conclusion, while you cannot directly “submit” your blog to ChatGPT or Gemini, you can create content that is easy for them to interpret and relay to users.

How does this differ from traditional SEO?

The distinction between traditional SEO and AI content processing lies in purpose and method. SEO is designed to help search engines like Google crawl, index, and rank your content so it appears when users type queries. In contrast, AI tools like ChatGPT and Gemini don’t rank pages; they interpret text to provide conversational responses.

What signals matter in SEO?

SEO relies heavily on technical and content-related signals:

• Backlinks from other websites act as votes of authority.

• Metadata (titles, descriptions, tags) helps search engines understand a page.

• Keyword placement ensures relevance to search queries.

For example, a travel blog optimised with backlinks from tourism boards and well-written meta titles may climb search rankings for “best beaches in Queensland.”

What signals matter for AI?

AI models don’t crawl or index the same way. Instead, they depend on:

• Clarity of writing – simple, structured sentences that models can summarise.

• Logical flow – headings, bullet points, and FAQs that guide understanding.

• Authority and trustworthiness – factual, verifiable content that reduces the risk of AI hallucinations.

For instance, an AI might prefer a blog that explains the steps of visa application clearly, rather than one that ranks well for “student visa tips” but is written in a keyword-heavy, confusing style.

Where the overlap exists

There is still common ground between SEO and AI optimisation:

• High-quality, original content is rewarded by both.

• Structured writing with headings improves discoverability and readability.

• Authoritative sources make both Google and AI more likely to use your content.

For example, a blog with a well-organised guide to “sourdough starter troubleshooting” can rank on Google due to its authority, and at the same time be summarised accurately by AI because of its clarity.

Why intent matters most

The ultimate difference lies in user intent. A Google searcher wants a list of results to explore, while an AI user expects a direct, conversational answer. This changes how your blog should be prepared:

• For Google: focus on visibility (rankings, clicks, traffic).

• For AI: focus on interpretability (clear, trustworthy answers).

To illustrate, a post titled “Ultimate Guide to SEO in 2025” may win in Google rankings if it’s keyword-rich and well-linked, but a concise post titled “Step-by-Step SEO Checklist” might be favoured in AI responses because it provides structured, digestible advice.

Wrap-up

Traditional SEO ensures you get found, while AI content optimisation ensures you get understood. Both are valuable, but together they create a future-proof strategy where your blog performs well in search engines and also gets surfaced by AI assistants.

FAQ

Do ChatGPT and Gemini index blogs like Google?
No, they don’t maintain an index. Instead, they process content when given access or when it’s part of their connected systems.

Can I optimise my blog for AI tools?
Yes – focus on clarity, structure, and authority so your content is easy for AI to summarise and cite.

Does Gemini read blogs in real time?
Not directly, but it uses Google’s search index to surface the most recent information.

Can ChatGPT find my new blog post?
Only if you provide it directly or if it’s connected via a plugin or API.

Is AI replacing SEO?
No. SEO still matters for visibility in Google, while AI visibility is an added layer that focuses on clarity and trustworthiness.