As we've always established, AI doesn’t “rank” brands. It recognises, evaluates and selects them.

When an AI system builds an answer, it asks itself a few quiet but ruthless questions:
- Do I understand what this brand is?
- Is it relevant to this exact question?
- Can I safely quote it without making things up?
- Have I seen it referenced elsewhere?

If any of those answers are uncertain, the brand gets skipped.

AI systems also work differently when it comes to which sources they choose. Almost 30% of the pages it cites have zero Google ranking, but rather come from UGC (user-generated content) sites like Reddit of YouTube. Perplexity’s algorithm, on the other hand, is closer to the traditional ones and it prefers citing sites with high authority. 

But even though AI systems work slightly differently, there are some things you can do that move the needle in general, no matter which AI assistant your audiences prefer:

1. Entity clarity & authority signals (aka: “What are you, exactly?”)
   
   AI systems need to understand what your brand is in one sentence before they can cite you. Brands that cited have:

   • Clear definition: who you are, what you do, what you’re known for

   • Consistent mentions across the web

   • Strong category signals (“SEO agency”, “e-commerce platform”, “consultancy”)

   • Verifiable proof points (press, awards, partnerships, credentials)

   Example: When someone asks "Best SEO agencies in the UK", AI platforms look for entities with strong signals in the "SEO agency" + "UK" space.
   
   

2. Contextual relevance (right answer, right moment)

   AI matches brands to specific questions, not general reputation. That means:
   - You might be cited for “AI search optimisation in the UAE”
   - But invisible for “global SEO strategy”
   - Or vice versa

Relevance is granular and AI is picky. Strong authority in the wrong context still equals silence.

2. Extractability 
   
   AI favours content it can use without effort. It prefers direct answers over vague commentary, clearly structured sections over long essays and explicit statements over clever phrasing. 
   
   If AI assistants need to interpret what you mean, they usually won’t. Make your content easy to lift, quote and recombine, not poetic.
   
   

3. Verifiable authority
   
   AI systems and engines avoid taking risks when it comes to recommending a brand, so they favour sources with:
   - Concrete claims instead of pompous adjectives
   - Experience-backed insight rather than generic advice
   - Signals that others already trust you, so reviews

So, to dominate your category, you need to focus your content strategy on original frameworks or methodologies, specific examples and outcomes, and recognisable third-party validation. 

 With AI Search, authority isn’t declared; it’s demonstrated and corroborated. 

4. Consistency across the web
   
   A coherent omnichannel content strategy is more important than ever because AI engines and assistants cross-check everything. If your corporate website says one thing, your LinkedIn say another, and directories say nothing at all, AI will hesitate in recommending you. Inconsistency doesn’t cause penalties; it causes indecision and that means you don’t get mentioned or cited.
    

5. Prompt alignment 
   
   AI can only cite what already exists. Brands show up when they’ve published content that mirrors how people naturally ask questions, covers topics deeply enough to handle follow-ups and uses language similar to conversational prompts.