Let's be honest and face the hard truth: AI is replacing traditional SEO.
And LLMs rank content almost the exact opposite way as traditional SEO. The strategies that worked for years—such as keyword optimisation and link building, are no longer enough. AI models prioritise different ranking signals that favour authority, relevance, and structured data. So, if your business depends on search traffic, you must adapt quickly. And if it doesn’t, this change presents a golden opportunity to establish visibility in a new and evolving landscape.
So... let's talk about making AI-native content.
How Do LLMs Rank Content vs. SEO?
Authority
Instead of backlinks, LLMs score authority based on mentions in credible independent places, such as:
- Scientific journals
- Reputable news outlets
- Industry-recognised blogs
Getting referenced in these sources signals to AI that your content is trustworthy and valuable. Unlike traditional search engines that measure authority through backlinks, AI relies on a broader contextual understanding of credibility. Brands looking to improve their AI visibility must invest in high-quality content that earns organic mentions in well-respected sources. AI models referencing peer-reviewed studies were 47% more likely to be cited.
Additionally, recent studies indicate that AI prefers content from government or institutional domains over commercial ones when assessing trustworthiness. This means businesses must invest in collaborations with universities or official organisations to increase their credibility.
Relevance
Traditional search engines rank based on authority, but AI models prioritise relevance above all else. LLMs interpret user intent as a sequence of questions aligned with the user’s ultimate goal rather than matching exact keywords. This shift has made long-form, deeply informative content far more valuable than simply matching search terms. Content providing comprehensive and direct answers is 62% more likely to be referenced in AI-generated summaries.
Unlike Google’s algorithm, which still depends on semantic indexing, AI models are increasingly trained to weigh user satisfaction over mere keyword density. This shift requires businesses to optimise for engagement and readability rather than just keyword positioning. Content structured around answering specific user queries with depth and clarity will perform better than generic, surface-level articles.
Links & Citations
LLMs won’t cite sources for general information (e.g. “what’s in vegan foie gras”), but they attribute unique or proprietary content, such as primary research or creative work. This means that creating genuinely new insights—whether through industry research, case studies, or first-hand analysis—will increase the likelihood of citation. Unique case studies and exclusive data-backed content were 78% more likely to be referenced.
For brands looking to increase citations, investing in exclusive white papers, experimental studies, or industry reports will drastically improve AI discoverability. Proprietary content that cannot be found elsewhere is a crucial driver for AI citation.
How to Gain Visibility in AI Models
1. Signal Authority
Get cited in respected publications and build a consistent online presence. Appearing in high-authority sources like academic research and news websites increases the likelihood of AI referencing your content. The more credible and well-structured your content is, the greater the chance AI will surface it in responses. Pages using structured data were indexed 38% faster.
Experts suggest that AI assigns higher weight to sites with long-standing domain authority. If you’re launching a new domain, accelerating authority-building through partnerships, guest posts, and co-branded research is essential.
2. Create AI-Native Content
Share original high-quality content, including:
- Proprietary data and research
- Case studies
- Opinion pieces
- Video transcripts and podcasts
Content incorporating multimedia elements performed 56% better in AI rankings. Additionally, regularly updating your content with the latest insights and statistics increases its likelihood of being referenced by AI models. Ensuring that your content remains fresh, data-driven, and optimised for AI enhances its authority. AI does not rank content based solely on when it was published but on how frequently it remains relevant, up-to-date, and useful.
Video and audio-based content is also becoming more essential. While AI struggles to parse audio alone, embedding structured metadata and transcription files allows search models to better interpret and cite non-text-based content.
3. Relevance
Since AI models treat user intent as a series of questions, structure your content in a long-form Q&A format. Think about all the questions a prospect might ask before they realise they need your product or service, and answer them in sequence. Content that mirrors the natural research process of a user is far more likely to be cited. LLMs show a 42% higher likelihood of referencing content that clearly segments information.
Moreover, structuring content with bullet points, headings, and subheadings helps AI models extract relevant data more efficiently, improving the likelihood of ranking in AI-generated search results. Information should be concise but comprehensive, breaking down complex subjects into digestible, well-organised sections.
AI also favours comprehensive knowledge graphs. If possible, structuring interconnected pages and linking them logically within an article will improve indexation and ranking in AI-driven search models.
4. Accessibility
Ensure AI crawlers can ingest your content by:
- Publishing on a publicly accessible website
- Providing transcripts for videos and podcasts
- Using structured data markup
Well-structured HTML increases AI crawlers' accuracy. Furthermore, avoiding duplicate content and ensuring each page provides unique insights will help prevent dilution of authority and increase the chances of being cited by AI. Emerging AI tools now scan for trust signals beyond structured markup. Features such as author verification, citation trails, and audience engagement analytics are playing an increasing role in AI indexing.
The Hard Truth
Some argue that “SEO isn’t dead, it’s changing.” But that’s often SEOs defending their profession. The smartest SEOs will evolve with these changes, but the traditional playbook won’t be enough.
The next 12-24 months are critical. Don’t get held back by the sunk cost fallacy. We know what works now: