How to Optimize Your Business for AI Search

TL;DR: Key Takeaways

• AI Search is a Core Channel: Generative AI assistants (like ChatGPT, Gemini, Perplexity) are no longer just tools; they are a primary customer discovery and acquisition channel.
• Clicks Are Not the Goal: Success in Generative Engine Optimization (GEO) is measured by Prompt Coverage (appearing in answers) and Citation Share (being the source), not just organic clicks.
• It’s “GEO + SEO”: AI Search optimization doesn’t replace traditional SEO; it builds on it. AI assistants still use Google, Bing, and YouTube to find information.
• Third-Party Content is King: AI assistants heavily favor editorial roundups, Reddit discussions, and community forums. Securing mentions on these “best of” lists is critical.
• Control the Narrative: Focus on building bottom-of-funnel content (product comparisons, “alternatives to” pages) because this is where AI assistants look for high-intent answers.
• Structure for Extraction: Use clean HTML, lists, and tables so AI can easily lift and cite your information accurately.

When ChatGPT launched in late 2022, few predicted it would fundamentally reshape customer discovery. What began as a tool for writing better emails has evolved into a significant acquisition channel. This evolution of AI Search has created a new customer journey, with some companies now reporting that 25% of new customers discover them through AI assistants.

Translation: if you’re not optimizing for AI search, you’re leaving money on the table. Here’s exactly how to fix that.

Why Are Clicks Declining Even as Visibility Increases?

For decades, we measured SEO success by organic clicks. Higher rankings meant more clicks, which generated more traffic and conversions. As a 25-year marketing veteran, I can tell you that playbook is yielding decreasing returns.

Since Google rolled out AI Overviews, search impressions have increased by approximately 49%, while click-through rates have dropped by around 30%. Your potential customers are getting answers directly from search results without ever having to visit your site.

The paradox is that you get more visibility but fewer clicks. While top-of-funnel informational queries are being absorbed into AI summaries, bottom-of-funnel branded searches—where users specifically mention your company name—are also appearing in these overviews. That’s essentially free brand advertising, but only if you’re showing up.

What Does the Modern AI Search Landscape Look Like?

In a post on X (formerly Twitter) on April 28, 2025, OpenAI announced that its AI search feature had exceeded one billion web searches in the preceding week. Add Google AI Summaries, AI Mode, Gemini, Perplexity, Claude, and other platforms, and you’re looking at a massive parallel discovery channel.

Despite the doomsday declarations that SEO is dead, AI assistants largely use the same ranking signals as traditional search engines, with additional weight given to third-party mentions and editorial sources. They’re indexing content from Google, Bing, YouTube, and other established platforms.

What’s changed the most is user behavior. AI search conversations are longer, more exploratory, and often represent late-stage buying intent that wouldn’t typically occur in traditional search. Your potential customers are having nuanced, multi-turn conversations about product comparisons and vendor evaluations—and if you’re not there, your competitors are.

What Is AI Search Engine Optimization?

AI SEO represents an evolution that optimizes for both conventional search engines and assistant-driven discovery. It’s essentially a combination of GEO (Generative Engine Optimization) and traditional SEO (GEO + SEO).

Given the fact that you shouldn’t be throwing the SEO baby out with the GEO bathwater, you should focus on three core objectives:

• Prompt Coverage: Ensure your brand appears in answers to questions your potential customers are actually asking.
• Citation Share: Maximize how often AI assistants cite your content as their source.
• Assistant Recall: Guarantee that when assistants reference your brand, they do so accurately.

You can track them with four key KPIs:

• LLM Share of Voice: Percentage of relevant prompts where your brand appears.
• Citation Share: Percentage of citations linking back to you.
• Accuracy Score: How often AI assistants correctly represent your facts.
• Platform Coverage: Your presence across YouTube, Reddit, LinkedIn, and other sources AI assistants reference.

The 7-Step AI Search Optimization Plan

Step 1: Track Your Baseline Visibility

You can’t improve what you don’t measure. Start by identifying 10-15 key prompts across your buyer journey:

• Problem-aware queries (“how to improve AI Search rankings”)
• Category queries (“best AI Search tools”)
• Comparison queries (“Your Company vs Competitor”)
• Alternative queries (“best alternatives to [competitor]”)
• Integration queries (“SEO tools for content teams”)

Action items:

1. Create a spreadsheet with these prompts.
2. Test each one across ChatGPT, Perplexity, Gemini, and Claude.
3. Note which brands appear, how often yours is mentioned, and what sources are cited.
4. Repeat this weekly to track changes.

You can spend time doing this manually or spend money by using an AI tracking tool like SEMRush AI Toolkit or Surfer SEO, which automate the process and provides deeper insights.

Step 2: Secure More Third-Party Mentions

AI assistants heavily favor editorial roundups, Reddit discussions, and LinkedIn articles over vendor content. When you find “best of” roundups where competitors appear but you don’t, take action.

Action items:

1. Compile a list of high-authority roundup articles in your category.
2. Identify the authors or editors.
3. Reach out with a personalized pitch explaining why your product deserves inclusion.
4. Be prepared for editorial requirements, affiliate partnerships, or sponsorship fees.
5. Track which placements lead to increased AI citations.

The long-term ROI of these placements—especially given their influence on AI citations—typically justifies the investment. One strategic placement can generate visibility for years.

Step 3: Create Content That Wins AI Citations

When AI assistants consistently cite competitor content instead of yours, the solution is straightforward: create better pages.

Action items:

1. Identify competitor pages that AI assistants frequently cite.
2. Analyze what makes them citation-worthy (comprehensiveness, structure, clarity).
3. Create superior versions with:
   • More thorough entity coverage.
   • Balanced perspectives, including potential drawbacks.
   • Clear, structured information that’s easy to extract.
   • Data and statistics that assistants can reference.
4. Consider publishing on high-authority platforms (LinkedIn, industry publications) in addition to your own site.

According to research on how LLMs retrieve information, clarity and comprehensive entity coverage significantly influence citation selection. Make your content impossible to ignore.

Step 4: Focus on Bottom-of-Funnel Content

AI assistants disproportionately rely on middle and bottom-of-funnel pages—product pages, comparison pages, and alternative evaluations.

When someone asks ChatGPT for software recommendations, the follow-up is typically “compare option A with option B.” If you haven’t published this comparison content, your competitors are controlling the narrative.

Action items:

1. Audit your existing bottom-of-funnel content.
2. Create priority pages in this order:
   1. Detailed product/service pages optimized for specific use cases.
   2. Head-to-head comparisons with your top 3 competitors.
   3. “Alternatives to [your product]” page (control your own narrative).
   4. “Alternatives to [top competitor]” pages where you’re featured.
   5. Category roundups where you can legitimately claim leadership.
3. Use templates for consistency (product comparisons, feature tables, pros/cons lists).
4. Update these pages quarterly with new data and insights.

This is where buying decisions happen. Invest accordingly.

FAQ

Which Platforms Do AI Assistants Trust Most?

Analysis of millions of AI-generated answers reveals assistants repeatedly pull from:

• YouTube: Tutorial content and product demonstrations.
• Reddit: Authentic user discussions and recommendations.
• LinkedIn: Professional insights and thought leadership.

These aren’t secondary channels—they directly shape AI responses. LLMs weight conversational and community-generated content heavily.

Action items:

1. Develop a multi-platform strategy:
   • YouTube strategy: Create 2-3 core tutorial or comparison videos monthly; optimize titles and descriptions for search.
   • Reddit engagement: Identify relevant subreddits; contribute genuinely helpful answers (no spam); link to detailed resources when appropriate.
   • LinkedIn publishing: Repurpose your best insights into LinkedIn articles; engage in relevant discussions; establish thought leadership.
2. Cross-promote content across platforms to maximize reach.
3. Monitor where your brand is mentioned and engage authentically.
4. Seed your perspective across these channels consistently.

How Should You Structure Content for AI Extraction?

This one isn’t new, just more important: assume that an AI will extract portions of your content without surrounding context.

Action items:

1. Use clean semantic HTML with proper heading hierarchy (H1, H2, H3).
2. Implement structured data (schema) markup where applicable.
3. Format key information as lists and tables (feature comparisons, pricing tiers, step-by-step processes).
4. Write with “context-inclusive language”—sentences that remain clear when excerpted.
5. Create short Q&A blocks that directly answer specific questions.
6. Include clear definitions for industry terms.
7. Use descriptive link text (not “click here”).
8. Add alt text to all images with relevant keywords.

Review your top 10 pages and retrofit them with this structure. Then make it your standard for all new content.

What Does a Weekly Measurement Cycle Look Like?

Build this into your weekly routine. Don’t let it become a quarterly “check-in.”

Weekly:

• Review your AI visibility metrics (run your prompt tests).
• Document changes in rankings, citations, and accuracy.
• Make 2-3 improvements: One new comparison or alternative page, an editorial outreach email, a video, or a cross-platform content piece.
• Track which changes correlate with visibility increases.

Monthly:

• Analyze patterns in your most successful content.
• Adjust your prompt tracking based on evolving customer language.
• Identify new high-value queries entering your market.
• Update your bottom-of-funnel content with fresh data.
• Review competitor visibility and adjust strategy.

The Winning Strategy for AI Search

Traditional search engines still command the vast majority of searches, but AI assistants are capturing an increasing percentage of discovery behavior, particularly for complex, high-intent queries.

A winning strategy combines two parallel efforts:

• Maintain SEO fundamentals: AI assistants index the same web that traditional search engines do. Strong technical SEO, authoritative backlinks, and comprehensive content remain essential.
• Optimize for AI extraction: Structure information for easy extraction, establish presence on platforms AI assistants trust, and proactively manage your brand narrative across third-party sources.

Companies implementing this approach are already seeing measurable results—up to 25% of new customer acquisition from AI channels. Those delaying risk losing visibility in an increasingly important discovery channel.

Start with Step 1 today. Track your AI Search baseline. You can’t optimize what you can’t measure.