Think in Entities, Not Just Keywords
Traditional SEO revolved around keywords. AI search revolves around context. Instead of matching strings of text, AI models interpret meaning – recognising entities such as people, places, products, and organisations, and how they relate to one another.
This means your website’s value to AI systems depends on how clearly it defines what you are, what you do, and how your content connects to broader concepts. Clean structure, consistent naming conventions, and semantic clarity all help AI models “understand” your business.
In practice: structure your content so every page has a clear purpose. Use consistent language when describing your services and organisation, and ensure that your brand, location, and expertise are easy to extract from your content.
Structure Content for Meaning, Not Just Layout
AI search thrives on relationships between ideas. A well-optimised site doesn’t just look organised – it signals structure. Headings, internal links, schema markup, and logical content hierarchies all help AI systems parse intent and relevance.
At Fahrenheit, we build what we call “semantic architecture” – clear hierarchies that map how each service, location, and topic connects to the next. This helps AI models identify your expertise and contextually associate it with relevant user queries.
Think of it as writing for a reader who’s also a machine – you’re guiding both toward understanding, not just visibility.
Create Expert-Led, Human-Centred Content
AI models reward authority. When your website demonstrates expertise through depth, clarity, and originality, it increases the likelihood of being cited, summarised, or surfaced in AI-driven search results.
That doesn’t mean writing for algorithms – it means writing content that’s genuinely useful to humans and verifiable to machines. Human insight, combined with structured presentation, is what differentiates meaningful content from generic filler.
In short: prioritise accuracy, transparency, and originality. If your content reads like something a professional in your field would reference – AI will likely do the same.
Strengthen Your Signals with Schema
Structured data (schema) acts as the translator between your content and AI understanding. It helps systems like Google’s SGE or OpenAI’s web crawlers contextualise your pages: who wrote them, what they describe, where they belong.
We use schema to define not just what a page contains, but what it represents – an organisation, a case study, a service, or an article. This ensures your content isn’t just indexed but understood.
For small businesses, even simple schema (Organisation, LocalBusiness, Service, Article) can make a measurable difference in AI visibility.
Build for Trust and Transparency
AI-driven search increasingly factors in reputation and authenticity. Verified contact details, author attribution, privacy compliance, and transparent communication about your business help signal trustworthiness.
It’s not enough to say who you are – you have to prove it through consistent, verifiable data. When AI systems encounter multiple signals that align (e.g. the same business details across your site, Google Business Profile, and structured data), they form a stronger “knowledge graph” of your brand.
Trust and technical accuracy are now two sides of the same coin.
Keep Your Site Fast, Accessible, and Maintainable
AI discovery still depends on foundational web quality. Slow, cluttered, or unmaintained sites lose crawlability and context. Accessibility – both for users and systems – remains a cornerstone of discoverability.
In our view, a website optimised for AI is simply a website built well: fast, secure, semantic, and designed to evolve.
The Takeaway
Optimising for AI search isn’t about chasing the next trend – it’s about preparing for a more semantic, context-driven web. Businesses that invest in clarity, structure, and authenticity today will be the ones most discoverable tomorrow.