Re-Optimising Your Blog Posts for AI Discoverability

Most blogs written before 2024 were designed for algorithms that ranked pages by keywords and backlinks. But the rise of AI-driven discovery tools has changed what visibility means.

Today, your content isn’t just competing for clicks in search results, it’s being evaluated, summarised, and sometimes quoted directly by AI systems like ChatGPT, Perplexity, and Google’s AI Overviews.

If your blog content was created before this shift, it’s likely underperforming in these new environments. Re-optimising for AI discoverability is about helping large language models (LLMs) understand, trust, and cite your work. That means focusing on clarity, source credibility, and semantic relationships rather than simple keyword density.

This guide explains how to update your existing posts so they not only perform better in traditional search but also gain visibility across AI-powered platforms shaping how people find and consume information today. 

Let’s get started.

Step 1: Identify Blogs Worth Re-Optimising

Start by auditing your existing content. Look for posts that:

• Rank well in traditional search but have declining traffic.
• Contain outdated references or statistics.
• Cover topics that overlap with trending AI search queries.

For example, if you wrote about “keyword optimisation” two years ago, revisit it to discuss entity recognition, LLM-friendly formatting, and semantic relevance. These updates help AI systems recognise the post as current and contextually rich.

You can use tools like Google Analytics to find declining web pages or Google Search Console to identify where search impressions are dropping.

Step 2: Strengthen Semantic Connections

AI systems evaluate how concepts relate to one another. A blog post that mentions “content optimisation,” “entity recognition,” and “semantic SEO” within clear context will likely be better understood than one that just repeats “SEO” several times.

Use keyword clustering (a method that groups related keywords) to map out topics surrounding your target term. For example, a cluster around “AI discoverability” might include “structured data,” “entity linking,” “knowledge graphs,” and “machine learning models.”

Make sure each of these ideas connects naturally in your writing. Rather than forcing keywords, build logical transitions between then. This makes the article flow naturally while enhancing it’s semantic depth, a key factor for LLM recognition.

Step 3: Improve Clarity and Structure for LLMs

LLMs process content by breaking it into tokens, which are basically small chunks of text that represent meaning. When your writing is cluttered, ambiguous, or overly complex, it increases the risk of misinterpretation.

To improve readability and token efficiency:

• Use short, declarative sentences.
• Add headings that describe what follows.
• Define technical terms inline (for example: “schema markup (code that helps search engines understand your content)”).
• Avoid jargon or vague phrases without context.

Structured data like Article or FAQpage schema helps reinforce meaning. It tells LLMs what your page is about and improves the chance of being cited in generative search results.

Step 4: Update and Cite Sources

AI systems prioritise recent and authoritative information. Replace outdated stats and references with newer, credible data from trusted industry-related sources.

Citations improve credibility, and LLMs are more likely to reference pages that include transparent source attritbution. Write citations in plain text and include a reference list at the bottom.

Step 5: Strengthen Internal Links and Context

Internal links help both users and AI understand how your content connects. When refreshing your content, look for ways to bridge related topics without repeating content.

For example:

If you are a local electrician and have a blog about signs your home needs rewiring, you could link to another blog post explaining how to choose a licensed electrician. You might write, “If you’ve noticed these warning signs, it’s important to hire the right professional — learn how to choose a licensed electrician in our detailed guide.”

This approach helps potential customers move naturally through your content while showing LLMs how your topics connect. It strengthens your authority, improves user experience, and builds clearer relationships between your pages, all key factors for AI discoverability and trust.

Step 6: Re-Publish, Request Indexing, and Monitor Performance

After updating, re-index the page using Google Search Console. Then monitor impressions, clicks, and engagement. Use tools like Perplexity or ChatGPT to test whether your updated post is being referenced or paraphrased in AI response.

Re-optimising for AI discoverability isn’t a one-time process. Treat it as part of your ongoing content strategy, ensuring your articles evolve with new search patterns and LLMs capabilities. 

As AI systems continue shaping how people consume content, re-optimisng your blog posts for AI discoverability ensures your work remains visible, trustworthy and cited. Focus on clarity, semantic depth, and up-to-date information. By aligning your optimisation efforts with how AI understands and recommends your content, you future-proof your digital presence.

If you’re ready to enhance your AI visibility and update your content for the next era of search, reach out to our team today.