Designing for Humans and Machines: Getting Visual Appeal and AI LLM Readability Right

Web design used to be a one‑way conversation: you designed for people, and search engines did their best to keep up. Today, every page you publish is read twice—once by a human, once by a machine. If you lean too far towards aesthetics, AI‑driven search struggles to understand you; if you over optimise for machines, real visitors feel like they’ve walked into a brochure written by a robot. The sweet spot is a site that feels effortless to use and looks on‑brand, yet is structured so algorithms can reliably interpret, rank and reuse your content

Two audiences, one experience

UX and SEO have traditionally pulled in different directions: UX tries to simplify life for people; SEO tries to simplify life for machines. In the AI era those lines are blurring.

Research and industry guidance highlight a few important shifts:

• Search engines and LLMs rely more on how users interact (dwell time, bounce, engagement) as quality signals, tying UX directly to visibility
• AI‑powered Assistants increasingly provide answers directly, so being machine‑readable isn’t just about rankings, it’s about your website being eligible to appear in the answer at all.
• Studies show that even small delays drastically increase bounce rates; pages loading in 5+ seconds can see bounce rates above 90%, directly undermining both UX and organic performance.

So the question isn’t “UX or SEO?” but “How do we design experiences that both people and machines can navigate confidently?”

Principle 1: Let structure carry meaning, design carry emotion

Underneath every beautiful interface is (or should be) a simple, logical skeleton. That skeleton -your headings, HTML structure and content flow—is what machines read first.

In practice:

• Use clear, semantic HTML (header, nav, main, section, article, footer) so that crawlers and assistive tech can understand the layout.
• Keep one unambiguous H1 per page, then step down sensibly with H2/H3 for sections and subsections.
• Write headings that describe intent, not design (“How our AI audit works” vs “Process”)​

Once that backbone exists, design can addpersonality—typography, colour, imagery, motion—without undermining how machines (and screen readers) understand the page.

A useful mental model:

• Structure = contract with machines about what lives where.
• Design = promise to humans about how it feels to use.

You honour both when you refuse to hide core meaning inside purely visual elements.

Principle 2: Use visuals to support, not replace, text

Visual storytelling - images, diagrams, video, animation etc can transform dry information into something memorable. It can also quietly erase you from AI search if it’s the only place key facts live.
To keep visuals and machine readability working together:

Treat images and video as illustrations of text, not containers for text.

• For important graphics (process diagrams, data charts, UI mock-ups), include a short HTML summary or caption that states the main point in plain language.
• Write alt text that describes purpose and outcome (“Diagram showing our three‑step audit process”) rather than stuffing keywords.

When visuals amplify what’s already written, LLMs can extract the message from your HTML, and humans get the emotional and explanatory boost that visuals provide.

Principle 3: Design for frictionless reading on any device

Most users now experience your website on a mobile screen; search engines factor that experience into how they rank and present your content. That makes responsive, readable design a machine‑readability issue as much as a UX one.

Evidence and best practice point to:

• Mobile‑first, responsive layouts that keep one URL per piece of content, rather than splitting desktop and mobile versions. This consolidates authority and simplifies crawling.
• Readable typography and contrast: sensible font sizes, line lengths and colour contrast dramatically reduce cognitive load for humans and improve accessibility signals for search.
• Lean, performant pages: compressed images, efficient code and limited animation keep load times down - something both users and ranking systems actively reward.

Principle 4: Treat navigation as a shared map for humans and machines

Site architecture is one of the few places where human and machine needs are almost identical: both want clear, predictable paths.

You strike that balance by:

• Using intuitive, descriptive menu labels (“Case Studies”, “Pricing”, “AI Search Services”) instead of brand‑specific jargon.
• Keeping depth sensible; research into UX‑SEO balance suggests flatter structures (fewer clicks to key content) improve both discoverability and usability.
• Supporting menus with breadcrumb trails and internal links that mirror real journeys (for example, from an article about AI search to an AI audit service page).​

For AI systems, a clear structure plus consistent internal linking makes it easier to understand which pages are authoritative on which topics. For people, it simply feels like “this site is easy to find my way around.”

Principle 5: Use content design, not just copy, to serve both audiences

Content design - that is how you break up information, order it and signpost it - is where machine readability and human comprehension meet.

Research on AI‑ready content and UX suggests a few practical guidelines

• Lead with the “why” and “what” at the top of the page, then unfold details. This matches how humans scan and how LLMs extract summaries.
• Break long explanations into short sections with descriptive sub‑headings and bulleted lists. These create natural “answer units” AI can quote.
• Group related concepts into clusters and link them together; semantic SEO research shows this helps both topic authority and AI interpretation.

You’re not just writing copy; you’re designing information so that a human eye and an algorithm can both say, “I understand what this is about and what to do next".

Principle 6: Performance as shared ground

One area where everyone agrees - UX specialists, SEOs and AI‑search researchers - is performance. Fast, stable pages improve every metric that matters.

Key levers include:

• Efficient coding and caching strategies that trim page weight without gutting design.​
• Smart media handling: compressing and properly encoding images and video so they enhance, rather than cripple, the experience.
• Proactive monitoring of Core Web Vitals as a joint UX/SEO KPI, not just a technical checkbox.

In other words, page speed isn’t an afterthought; it’s part of how you respect both your human visitor’s attention and the machine’s resource limits.

Principle 7: Design with AI as a downstream user

The emerging research on AI‑powered content and LLM‑assisted UX highlights a subtle but important shift: your website is no longer always the “final interface”.

LLMs increasingly:

• Pull snippets of your content into chat answers
• Generate UI elements in other environments based on your documentation
• Evaluate layouts and flows for usability using multimodal models.

To prepare for that reality:

• Make sure your most important claims and explanations exist as clean, standalone text segments.
• Write micro copy (button labels, error messages, tooltips) with the expectation it may be quoted in another interface.
• Keep your terminology consistent across pages so AI systems can build a coherent picture of your services.

You’re designing not just for the user in front of your site, but for the AI that might retell your story somewhere else.

Selected sources

• AWA Digital : “UX Design vs SEO: Balancing User Experience and Search Visibility”
• Search Engine Land : “SEO and UX: Finding the strategic balance for optimal search visibility”
• Nomensa : “How UX affects SEO”
• Ahrefs : “UX and SEO: A guide for winning the searcher, not just the algorithm”
• Strapi : “What is machine‑readable content?”
• Newsdata.io : “How to make your content LLM‑ready for better AI search ranking”
• SurferSEO : “LLM‑friendly content: tips to get cited in AI answers”
• Zion & Zion : “AIO, SEO, and UX – finding the right balance in modern content strategy”​
• ARXIV “The role of large language models in UI/UX design” (systematic literature review)

FAQ's : UX,Visual Design and AI Readability

Q1. Can I prioritise UX and still be machine‑readable?

Yes. Research shows that many UX best practices—clear navigation, readable
typography, fast load times—directly support SEO and AI understanding when
paired with semantic HTML and consistent structure.

Q2. Do I need to redesign my site to improve machine readability?

Not always. Many gains come from restructuring headings, simplifying navigation, improving content chunking and adding structured data - changes that can sit within your existing visual design system.

Q3. How much visual flair is “too much” for SEO and AI?

Problems usually arise when key information lives only inside heavy animations, complex scripts or image‑only layouts. If core messages are available as clean text and pages remain performant, you can safely layer in visual richness.

Q4. How does mobile design affect both humans and machines?

Mobile‑first, responsive layouts improve usability on phones (where most traffic now lives) and consolidate SEO signals into a single URL, simplifying crawling and ranking for search and AI systems.

Q5. What’s the quickest win to improve both UX andmachine readability?

For many sites, fixing heading hierarchies and simplifying page layout -shorter sections, clearer sub‑headings, better internal linking - immediately helps visitors scan and makes it easier for LLMs to extract accurate, self‑contained answers.

Q6. How can web‑aviso help with this balance?

web‑aviso can co-ordinate a combined UX, SEO and AI‑visibility audit of your site, then propose a phased plan that protects your visual identity while strengthening the structural, content and performance signals machines rely on to understand and recommend you.

Want your site to delight humans and make sense to machines?