Monthly SEO Insights: February 2026

If you’ve been following our insights over the past few months, you’ll have noticed a common thread that informs everything we’re seeing: search is quietly but firmly changing shape. Over the past month, we’ve seen even more evidence that the industry is shifting away from just “ranking pages” and instead towards “retrieving answers.”

Three key developments stand out based on this past month’s insights:

• AI visibility is beginning to surface in search performance dashboards
• Cloudflare launching a new feature to serve simplified Markdown pages to AI agents
• The growing debate around “chunking” content for Large Language Models (LLMs)

All three point in the same direction: search is increasingly about retrieving the right answer quickly, not just surfacing a list of links. What that means in practice is worth unpacking.

1. Bing Webmaster Tools Launches AI Performance Dashboard

While much of the industry conversation centres on Google, Microsoft has taken a notable step within Bing Webmaster Tools. It announced, in February, the launch of AI performance data connected to AI-driven search experiences. The dashboard shows how many times your content has been cited as a source in AI-generated answers, which specific pages are being referenced most often, and the search phrases the AI agent used when it retrieved your content – what Microsoft calls ‘grounding queries’.

In simple terms, we’re moving beyond the question of “Where do we rank?” and towards “Are we being referenced by AI?”

If an AI system generates an answer and cites your business, that visibility may, in time, start to carry more authority than a traditional “blue link.” For smaller, local businesses, this is quietly encouraging.

AI models don’t favour the brands with the biggest marketing budgets; they favour clarity, structure, and demonstrable expertise. Google Search Console, for now, doesn’t offer an equivalent report or dashboard where you can view AI performance, like it does with traditional search. However, with Microsoft leading the way so far, the pressure on Google to follow suit is growing. It’s a question of when, not if.

What we are doing now

Using our proprietary ARTEMIS INTELLIGENCE® methodology, we are stress-testing key service pages to ensure they:

• Lead with clear, “extractable” definitions
• Address the main search intent early, so both users and AI find what they need without digging
• Are formatted for clarity and discoverability (i.e., built with clean hierarchy, logical flow, and schema markup)
• Contain context, reasoning, and expertise that proves you know your subject

2. The Cloudflare “Markdown” Signal

One of the more technical developments this month comes from Cloudflare, which has launched a new feature called Markdown for Agents. The idea behind it is straightforward: a typical webpage is full of HTML, CSS and JavaScript that a human browser needs, but that an AI agent doesn’t necessarily. All of that clutter has a cost.

Basically, AI processes text in units called tokens, and wading through line after line of unnecessary code can burn through their token allowance quickly.

Cloudflare’s solution automatically converts the HTML into clean, stripped-back data before serving it to an AI agent, whenever it requests a page.

Why does this matter?

This doesn’t mean you need to rebuild your website at all to contain Cloudflare-friendly code. However, it does reinforce advice that we’ve given for years, and that’s how strong technical website foundations are essential.

If an AI agent struggles to “read” your website content due to bloated JavaScript, messy or disorganised code, then it’s not going to be able to recommend you in search results.

We are continuing to audit our clients for:

• Crawl accessibility – removing the “fog” that prevents AI from seeing your content
• Semantic hierarchy – ensuring your headings tell a clear, logical story that AI can follow
• Rendering efficiency – auditing your site load speeds to check whether they load quickly enough for AI agents to retrieve it, because a slow, bloated site risks being ignored entirely

3. Creating Content for LLMs

Perhaps the most debated topic this month is how to “chunk” content for Large Language Models (LLMs). As AI retrieves information in segments, it can be tempting to break all your content into short, sharp fragments.

But the truth, as ever, is that there’s a fine balance to strike.

The sweet spot, in our experience, is content that does both: answers a question clearly and quickly, then provides the depth and context that demonstrates real expertise.

Think of it like answering a client face-to-face; you give them the short answer first, then back it up. That means leading with a concise, “extractable” definition that an AI can easily cite, following it with the expert reasoning and context that only your business can provide, and maintaining a consistent voice throughout that builds trust over time.

What This All Means for Your Business

Run these three developments together and a consistent picture emerges. AI systems don’t browse websites the way a human does, they retrieve specific information, synthesise it, and present an answer. That changes what it means to be visible online. It’s no longer just about where you rank; it’s about whether your content is clear, structured, and credible enough to be a source that an AI chooses to cite.

For the businesses we work with, this is genuinely encouraging. When your expertise is clearly articulated and your site is technically sound, you’re not just competing for rankings, you’re becoming the source that AI refers people to.

Does your current strategy focus on being “ranked” or being “referenced”? If you’re not sure, get in touch for an AI-readiness audit.