How to Build Your Web Presence for AI Discovery

Probably the most talked about subject in the field of UX and Marketing. There is a fundamental shift in how brands are discovered digitally. For more than two decades, organisations have optimised their websites for two audiences, people and search engines.

Today, there is a third audience. AI systems.

Before I proceed, just a clarifying statement. When I mention your website in this article, it could refer to your individual website, your brand, or your organisation’s website.

Increasingly, the first conversation a prospective customer has about your organisation occurs within an LLM such as ChatGPT, Gemini, Claude, Perplexity, or another AI assistant. Before they visit your website, those systems may have already summarised your capabilities, compared you with competitors, and influenced whether you make the shortlist.

Your website is no longer just a digital brochure. It is becoming part of your organisation’s knowledge infrastructure, and that knowledge infrastructure not only needs to be available to AI crawlers, but the AI engine also needs to understand it and recommend with confidence.

The Discovery Economy Has Changed

Traditional Search Engine Optimisation (SEO) focused on one objective. Earn the click by capturing the user’s intent. AI-assisted discovery changes that objective. It’s not only capturing the intent; increasingly, the recommendation happens before the eventual visit to the branded online presence. Users ask AI assistants to recommend consultants, compare software platforms, explain technical concepts, identify suppliers, and shortlist agencies. Rather than pointing users to ten blue links, AI systems synthesise information from multiple sources before generating an answer.

You may have heard this a zillion times in the past few months that SEO is not disappearing but evolving. Alongside SEO, a new discipline is emerging. Depending on who you ask, it is called AI Engine Optimisation (AEO), Generative Engine Optimisation (GEO), AI Search Optimisation, or LLM Optimisation.

While the terminology is still evolving, the objective is clear. Help AI systems not only understand your organisation accurately but also recommend shortlists when requested.

Your Website Has Become a Machine-Readable Knowledge Asset

Your website is increasingly a machine-readable knowledge asset, which means every product or service page, executive biography, framework, customer testimonial, case study, FAQ, research paper, and, if relevant, ecommerce pages.

Together, they create the digital representation of your organisation that AI systems use to understand your brand or personal expertise.

The organisations that succeed will not simply publish more content. They will publish clearer, better-structured knowledge.

A Simple Framework for AI Discovery

As I have been thinking about this shift, I keep coming back to one observation. AI systems do not appear to build confidence from a single/ few webpages. They build confidence by comparing multiple parameters and intentional structure.

At a strategic level, I believe every organisation should ask three questions.

1. Who do you say you are?

This is your identity. It is everything you publish about your organisation. Your website, services, product, methodologies, leadership team, intellectual property, executive profiles, blogs, FAQs, original research and much more. The clearer and more structured your knowledge becomes, the easier it is for AI systems to understand who you are.

2. How do you prove your capabilities?

Claims create awareness, and evidence creates confidence. Every organisation says it is innovative, customer-focused, or industry-leading. The organisations that stand out demonstrate it.

The Evidence includes:

• Customer testimonials.

• Case studies with measurable outcomes.

• Client success metrics.

• Published methodologies.

• Awards and certifications.

• Research and white papers.

• Customer videos.

• Before and after business results.

• Product demonstrations.

• Implementation examples.

The stronger your evidence, the easier it becomes for AI systems and prospective customers to associate your organisation with real expertise.

3. What do others say about you?

This is independent validation. AI systems rarely rely on a single source. Instead, they compare information from multiple trusted sources to determine whether your claims are consistently corroborated elsewhere.

Validation may include:

• Media coverage.

• Industry publications.

• Conference speaking engagements.

• Podcasts and interviews.

• Professional associations.

• University affiliations.

• Analyst reports.

• Partner websites.

• Professional profiles.

• Customer reviews.

• Industry directories.

• Social Media coverage

• Third-party review services

Trust grows when other people tell your story. That’s why earned media is making a big comeback.

Introducing the Evidence Stack

As I looked at these different forms of validation, another idea emerged. Not all evidence carries the same weight.

Instead, organisations should think about building an Evidence Stack, a collection of complementary credibility signals that reinforce one another.

Layer One, Organisational Evidence

The evidence you publish yourself.

• Services.

• Methodologies.

• Frameworks.

• FAQs.

• Executive profiles.

• Original research.

Layer Two, Customer Evidence

The evidence was created through successful delivery.

• Testimonials.

• Case studies.

• Customer reviews.

• Client logos, where permission has been granted.

• Measurable business outcomes.

• Video testimonials.

Layer Three, Market Evidence

Recognition from your industry.

• Awards.

• Certifications.

• Conference speaking.

• Media mentions.

• Podcasts.

• Industry publications.

Layer Four, Ecosystem Evidence

Validation from the broader professional community.

• Partner websites.

• Professional associations.

• Academic institutions.

• Industry directories.

• Standards bodies.

• Relevant open source contributions.

Every additional layer increases confidence.

Not because a single signal is decisive, but because consistent signals from multiple trusted sources reinforce one another.

The Technical Foundations

None of this removes the importance of technical implementation.

It makes it even more important.

The underlying architecture of your website should help machines understand your expertise as clearly as humans do.

That includes:

• A logical information architecture.

• Clearly defined entities and relationships.

• Structured content.

• JSON-LD schema.

• Strong internal linking.

• XML sitemaps.

• Appropriate crawl permissions for AI crawlers.

• An llms.txt file where appropriate, recognising that it remains an emerging convention rather than an established web standard.

Think of these as translation tools that do not create authority but help machines interpret authority, or put another way:

A schema does not create trust. It translates trust into machine-readable language.

A Discovery Readiness Checklist

Ask yourself a few simple questions, then maybe run some experiments based on them in the LLM ecosystem.

1. Can an AI system clearly understand what your organisation does?

2. Have you documented your methodologies rather than simply describing your services?

3. Are customer outcomes visible and measurable?

4. Are testimonials attributed wherever possible?

5. Do independent sources reinforce your expertise?

6. Is your structured data complete?

7. Can AI crawlers access your most valuable content?

8. Does every important page reinforce the others through logical relationships?

9. Would an AI assistant confidently recommend your organisation based on the information available today?

10. Which questions, phrases, categories, services, or products do you want to have a good SOV in?

Final Thoughts

For years, organisations competed for clicks. Over the next decade, they will increasingly compete for confidence.

The winners will not necessarily be those with the largest marketing budgets or the highest content volume.

They will be the organisations that build the clearest identity, provide the strongest evidence, and earn the broadest independent validation.

Because AI systems are not simply searching the web.

They are increasingly helping people decide who they can trust.

The organisations that make trust easier to understand, verify, and communicate will be the ones most likely to be discovered.