Over the past few months, there’s been an explosion of excitement and confusion around AI-powered search: GEO (Generative Engine Optimization), LLMO (Large Language Model Optimization), and AEO (Answer Engine Optimization). Everyone’s scrambling to figure out how to “rank” in ChatGPT, Claude, Perplexity, and the next-gen AI tools that are rapidly reshaping search as we know it.
After running extensive tests across multiple websites for 7 months, here’s the core insight:
AI visibility is built on classic SEO fundamentals.
The same principles that help you rank on Google are what get you cited, mentioned, and surfaced in AI search experiences. While the platforms and interfaces may be new, the mechanics are surprisingly familiar.
Let’s dive into the 7 fundamental pillars of SEO that directly power your brand’s presence in AI-generated results.
Table of Contents
1. Build Trust Signals in All the Right Places
AI systems assess credibility through patterns—especially review platforms, brand mentions, and third-party validations.
What You Should Do:
- Local Businesses: Optimize your Google Business Profile (GBP). Encourage genuine reviews, respond professionally, and update your info regularly.
- SaaS Brands: Focus on G2, Capterra, and Product Hunt. Keep your product descriptions and company profiles current.
- Ecommerce Brands: Leverage Trustpilot, Sitejabber, or industry-specific review aggregators. Highlight testimonials and verified user feedback.
Pro Tip: AI tools often favor businesses that show active engagement with reviews—so don’t just collect them, respond with context and care.
2. Structure Content for AI and Humans Alike
Unlike traditional search crawlers that extract keywords and tags, LLMs parse context and appreciate clarity in document hierarchy.
Best Practices:
- Replace vague references like “our update” with specific phrases such as “Acme Corp’s Q4 2024 Product Update.”
- Use descriptive H2s and H3s that are easy to parse and meaningful on their own.
- Present information in multiple formats: bulleted lists, comparison tables, and inline facts.
Think of each section as a standalone resource AI tools can pull from and reference. This makes your content more modular and AI-ready.
3. Link Building for Relevance (Not Just Authority)
Gone are the days when quantity trumped quality. AI search prioritizes contextual relevance and domain alignment.
Tactics to Focus On:
- Secure backlinks from industry-specific blogs, forums, and digital magazines.
- Collaborate with thought leaders or brands in your vertical.
- Don’t ignore nofollow links—AI models often treat these as signals.
- Seek brand mentions even when they’re not linked. LLMs extract brand authority from unlinked references too.
Avoid backlink schemes or irrelevant sources. If it doesn’t make sense for your niche, it won’t help—and may even harm—your AI credibility.
4. Become a Topical Authority in Your Niche
AI systems look for patterns of depth, not just breadth. Publishing tons of general content doesn’t help if it’s off-topic.
What to Do:
- Focus on building deep, authoritative content in a specific niche.
- Prune or remove unrelated blog posts that dilute your domain’s theme.
- Use content clusters, internal linking, and pillar pages to signal authority.
Remember: LLMs are trained on the same open web Google uses. If your content is too scattered, you’re less likely to be recognized as a go-to source.
5. Be Everywhere AI Crawlers Are
Want to increase your brand’s footprint in AI outputs? Then you need to show up on platforms where LLMs gather data.
Key Platforms:
- Reddit: Participate in niche subreddits or start AMA threads.
- LinkedIn: Share insights and publish long-form posts.
- Medium: Syndicate your blog content to a broader audience.
- YouTube: Include detailed descriptions and transcripts for indexing.
Repurposing content across these platforms increases the chance of multiple mentions, which reinforces your brand’s relevance in AI models.
The more consistently you appear across trusted platforms, the more AI tools infer you’re an authority.
6. Technical SEO Still Matters—A Lot
Even in the age of AI, your site’s technical foundation remains critical for visibility.
Checklist:
- Use clean HTML (avoid JavaScript-heavy rendering when possible).
- Implement structured data/schema markup to help AI interpret your pages.
- Maintain a logical site architecture (no important page should be more than 3 clicks away).
- Ensure fast loading speeds and server-side rendering for key content.
AI crawlers aren’t magic—they still rely on the same underlying signals as traditional search bots. A broken or bloated website won’t perform well, regardless of your content.
7. Traditional Search Signals Feed AI Engines
Most AI search platforms rely on Google or Bing’s index to source and validate real-time web data. In other words:
If you don’t rank well in traditional search, your AI visibility is already limited.
LLMs reference top-ranking content as training and response material. So if your content isn’t ranking on Google, it’s unlikely to be cited or surfaced by ChatGPT or Perplexity either.
Double down on:
- Core Web Vitals
- On-page SEO (title tags, meta descriptions, internal linking)
- Semantic content and FAQ blocks
Maintain a solid presence in search engines—it’s the foundation upon which AI search builds.
Final Thoughts: Shine Where It Matters
The hype around LLMO, GEO, and AEO is real—but success in these areas comes not from gimmicks, but from doing the fundamentals exceptionally well.
If you’re building:
- Trust through real-world signals
- Authority through niche depth
- Clarity through well-structured content
- Presence across AI-crawled platforms
…then you’re already ahead of the curve.
Avoid distractions from shiny “AI hacks.” Focus instead on creating content and experiences that both search engines and intelligent models want to surface.
AI search isn’t a new game. It’s just the next level of the same one.