How Is AI Changing The Way We Think About Web Design And SEO?

How Is AI Changing The Way We Think About Web Design And SEO?

Are You Asking Yourself ‘How Is AI Changing The Way We Think About Web Design And SEO?’ The advent of artificial intelligence (AI) has fundamentally transformed the digital ecosystem, particularly in how users discover and interact with online content. As AI-powered search tools like Google’s AI Overviews, ChatGPT, Perplexity, and Gemini become primary gateways for information, traditional web design principles are being challenged. What was once a focus on keyword-stuffed pages and linear user journeys is now evolving into a need for machine-readable, context-rich experiences that AI can easily parse, cite, and recommend. With over 58% of Google searches ending without a click due to AI-generated summaries, websites must now prioritize visibility in conversational AI responses over mere organic rankings. This shift, accelerated by large language models (LLMs), demands that companies and designers rethink web design to remain relevant. In this article, we explore AI’s impact on web design and SEO, adaptation strategies for businesses and designers, best approaches to creating AI-ready websites, and practical tips for updating existing ones, backed by recent research and examples.

AI’s Impact on Web Design and SEO: A Paradigm Shift

AI is reshaping search and discovery in profound ways, moving from keyword-based queries to natural language conversations where users expect direct, synthesized answers. Traditional SEO, which optimized for SERPs (Search Engine Results Pages), is giving way to Generative Engine Optimization (GEO) and LLM Optimization (LLMO), where content must be “AI-proof”—structured for easy extraction and citation by AI systems. For instance, Google’s AI Overviews (AIOs) now appear in 43% of responses, mentioning brands only 43% of the time with 30x higher volatility week-to-week, while AI Mode surfaces brands in 90% of cases but with 3.8x more unique brands overall. This volatility erodes traffic: Pew Research’s March 2025 study of over 900 adults found that only 8% of users encountering an AI summary clicked a website link, compared to 15% for standard search results, with 26% of AI summary sessions ending browsing entirely.

For web design, this means sites must transcend visual appeal to become “trusted answers” in AI ecosystems. LLMs like ChatGPT (with 700 million weekly active users) and Perplexity (22 million in May 2025) pull from knowledge graphs, search results, and conversational data, favouring content that’s semantically connected and authoritative. However, AI’s derivative nature—often hallucinating or recycling generic content—amplifies the value of original, high-effort material. A 2024 Siege Media study of 50 sites showed whole-site clicks down 4.8%, but homepage visits up 10.7%, attributed to branded searches and AI-driven navigational traffic. Ecommerce faces unique challenges: AI acts as a “sales rep,” filtering products based on context, reducing direct PDP (Product Detail Page) visits as users rely on summaries.

In B2B and local contexts, AI favours structured, intent-driven content like comparisons and FAQs, with sources in AI Overviews matching top 10 organic results 99.5% of the time—often requiring just 13 referring domains for inclusion. Yet, LLM traffic (under 1% of sessions) converts at 4.87%, similar to organic’s 4.6%, underscoring the need for scale alongside quality. Overall, AI erodes the web ecosystem by concentrating traffic on giants like Wikipedia (15% of AI citations), YouTube, and Reddit, leaving smaller sites vulnerable unless they adapt.

How Companies and Designers Need to Adapt

The AI era requires a proactive pivot: from optimizing for humans and algorithms to educating AI systems with clear, credible, and deliverable content. Google’s John Mueller affirms that AI won’t replace SEO as long as websites exist, especially for ecommerce and local businesses where direct interactions (e.g., purchases) remain essential. Companies must build “content knowledge graphs” using schema markup to define entities (products, services, people) and relationships, making sites machine-readable for LLMs.

For Companies:

• Audit AI Presence:

  Use “Temperature 0.0” prompts in tools like ChatGPT (e.g., “[Your Business Name] is known for”) to gauge how AI perceives your brand, revealing gaps in entity clarity. A SEMrush study shows AI visitors convert 4.4x better than organic ones, so prioritize site health for crawlability.

• Foster Authority:

  Invest in original research (e.g., BoundlessHQ’s remote work survey cited by AI) and high-effort content to earn citations, as AI prefers non-derivative sources. For ecommerce, gather user context from Reddit or Quora to inform PDPs, as AI mediates 60%+ of collection page traffic.

• Diversify Sources:

  Syndicate thought leadership on Medium or Dev.to with canonical links back to your site, and encourage detailed reviews mentioning outcomes (e.g., “fixed the problem immediately”).

For Designers:

• Embrace GEO/LLMO:

  Shift from keyword stuffing to conversational, natural language content that answers full user queries (e.g., “Where can I make a reservation for authentic Italian food near Union Station that’s good for date night?”). Use tools like SEMrush AI Tracking to monitor citations.

• Prioritize Machine-Readability:

  Design with semantic HTML5, proper headings, and avoid JavaScript-heavy rendering, as AI bots like GPTBot may skip it. Google’s June 2025 Knowledge Graph update emphasizes entity clarity, so unify ambiguous entities (e.g., people, products).

• Ethical Focus:

  Disclose AI-generated content and prioritize human-written material, as LLMs detect and deprioritize synthetic outputs. For B2B, create comparison pages with pros/cons/pricing, as Gemini favours them in 90% of responses.

Adaptation is urgent: AI search could surpass traditional traffic by 2028, and early movers in GEO see 3.8x more brand mentions.

Best Approaches to Website Design in the AI Era

Designing AI-ready websites means creating experiences that serve both humans and machines: clear, structured, and contextually rich. The ALCHEMY framework (Audience research, Learning/audit, Clarify aim, Hierarchy, Essential features, Mapping, Yield) provides a blueprint for this.

Core Principles:

• Semantic Structure and Crawlability:

  Use semantic HTML5 elements (e.g., <figure>, <table>) over images for data, as AI scrapers prefer raw HTML. Implement llms.txt files to guide AI crawlers and avoid blocking bots like GPTBot in robots.txt. For ecommerce, Shopify’s duplicate URLs leak equity; fix by canonicalizing to main product URLs.

• Structured Data and Schema Markup:

  Apply Schema.org types (FAQPage, HowTo, Product, OfferCatalog) to make content machine-readable. Google’s Mueller notes schema aids features but not direct rankings—yet it’s vital for AI citations, matching 99.5% to top organic results. For PDPs, add “Ideal for…” context (e.g., “Perfect for multi-day backpacking trips down to -20°C”).

• Conversational and Multi-Format Content:

  Structure for chunk-level retrieval: self-contained sections with H2/H3 headings, bullet points, tables, and natural Q&A. Use topic clusters (pillar pages linking to spokes) to build authority, as in a retirement company’s “Understanding 401Ks” hub. For B2B, favor comparisons (e.g., “X vs. Y”) and integration docs, cited frequently by Gemini.

• Performance and UX Optimization:

  Aim for <2-second loads (0.1-second improvement boosts conversions 10%), using lazy loading and WebP images. Ensure accessibility (alt text, keyboard navigation) for AI and users. For local SEO, add geo-specific schema and event details to GBP-linked pages.

Examples: Sentry’s API docs are cited by ChatGPT for backend metrics; Vanta’s SOC 2 page appears in startup compliance queries. Shopify stores with schema-enhanced collections see 60%+ organic traffic from category pages.

Adapting Existing Websites: Practical Steps and Examples

Retrofitting sites for AI requires audits and iterative updates, focusing on entity clarity and machine-friendliness.

Step-by-Step Tips:

1. Audit for AI Readiness:

   Disable JavaScript and test crawlability; use “Temperature 0.0” prompts to check AI perception (e.g., for a moving company, AI buried it behind competitors in “moving to Birmingham, AL”). Tools like Semrush AI Optimization reveal blockers.

2. Implement Structured Data:

   Add schema to PDPs (e.g., Product with audience/usageInfo) and FAQs; for Shopify, use Custom Liquid blocks for OfferCatalog on collections. Update pillar pages as “entity homes” (e.g., consolidate 401K content).

3. Enhance Content with Context:

   Role-play AI conversations (e.g., Claude simulating a Toyota buyer query) to add “who it’s for” details; refresh with “last updated” timestamps. For B2B, add pros/cons/pricing to comparisons.

4. Fix Technical Issues:

   Resolve duplicates (e.g., Shopify’s /products/ vs. /collections/ URLs via canonicals and GSC removals); optimize speed with Crush app. Use llms.txt for crawler access.

5. Monitor and Iterate:

   Track AI citations with SEMrush or Ahrefs Brand Radar; consolidate redirects to preserve link equity (99.58% of featured snippets rank top 10). For local, audit NAP and add service schemas.

Examples: ReMarkable 2 PDP added Reddit-sourced FAQs like “Is it a realistic notebook alternative?”; Vanta’s compliance hub cited in ChatGPT for startups. A 0.1-second speed tweak lifts conversions 10%; schema makes content eligible for AI features.

Conclusion: Embracing AI as an SEO Opportunity: How Is AI Changing The Way We Think About Web Design And SEO?

Web design in the AI age is about becoming the “trusted answer” across ecosystems, not just SERPs. By adapting with structured, context-rich designs, companies can mitigate traffic losses (e.g., 4.8% site-wide clicks down) and capitalize on AI’s 4.4x conversion edge. Designers must prioritize semantic, performant sites; businesses, original authority. As AI evolves, ongoing audits and human-centric content will ensure resilience—AI won’t replace SEO, but ignoring it will. Start with a knowledge graph audit and schema implementation to future-proof your site today.