The AI Search and AEO Experts to Follow in 2026

AI search has changed how buyers find information. A June 2026 SparkToro/Similarweb study found that 68% of US Google searches ended without a click. In 2024, Gartner predicted that traditional search volume would drop about 25% by 2026 as users shift to AI answer engines. Buyers now ask ChatGPT, Gemini, and Perplexity for recommendations instead of scrolling through search results. Platforms like AirOps track which questions those buyers ask before they reach your site.

Answer engine optimization (AEO) focuses on earning citations and mentions in AI-generated answers. Generative engine optimization (GEO) is a related term describing strategies that help content surface inside LLM responses. Both disciplines have emerged fast, and the practitioners shaping them are worth your attention. The work they publish shows you what signals LLMs look for when deciding which brands to cite.

The experts on this list teach you what to do once you have that signal. Here are 6 AI search and AEO experts whose work will help your team stay visible where buyers are looking. Each has joined an AirOps webinar where they break down their approach, so you can watch them in action.

What makes a credible AEO expert

A credible AEO expert publishes verifiable methods and real results, not hot takes. The field is young, so look for people who back claims with data and explain their reasoning in ways you can test yourself. Opinions are easy to share. Documented experiments and real outcomes separate the credible from the noisy.

• They publish original research, studies, or datasets on AI search behavior.
• They name specific frameworks or methodologies you can apply.
• They show real client outcomes, platform changes, or documented experiments.
• They teach consistently across newsletters, conferences, or courses.
• They are transparent about what they don't know and where the field is still evolving.

Signals like E-E-A-T (experience, expertise, authoritativeness, trustworthiness) apply to people the same way they apply to content. An expert whose work is cited by others and who has a track record of accurate predictions earns credibility over time. When evaluating any AI search expert, ask yourself: can I test this advice, and does it hold up against what I see in real results?

How we chose these AEO experts

We cross-referenced the major 2026 lists ranking AI search and SEO practitioners, verified each person's published work, and confirmed they remain active this year. Independence mattered: no self-insertion, no paid placements. We also looked for diversity of focus areas so the list covers strategy, technical implementation, and measurement.

• We prioritized breadth: strategists, technical specialists, and measurement-focused educators all made the list.
• We excluded anyone whose expertise could not be verified through public sources.
• We did not accept payment or consideration from anyone listed.

The 6 AI search and AEO experts to follow in 2026

Aleyda Solís, Mike King, and Lily Ray appear on nearly every 2026 list for good reason: each publishes original work, teaches actively, and has documented results. All six experts on this list have joined AirOps webinars where they share their methods. The list spans two groups so you can find the experts whose specialty matches your needs.

Strategy and growth voices

These three experts set the strategic foundation for AI search optimization. Their work helps you understand where the field is heading and how to build a long-term approach.

Aleyda Solís is an SEO and AI search optimization consultant and founder of Orainti. She created the SEOFOMO newsletter and LearningSEO.io, a free resource offering AI search optimization and SEO learning roadmaps. Follow her for strategic frameworks you can apply across industries. She breaks down her full AI search action checklist on the AirOps webinar below.

Kevin Indig is an independent organic growth advisor who previously led SEO and growth at Shopify, G2, and Atlassian. His Growth Memo newsletter publishes research-backed AI visibility studies. Follow him for insights on connecting AI search to business outcomes. He dives into the ChatGPT versus Google landscape on the AirOps webinar below.

Eli Schwartz is a growth consultant and author of "Product-Led SEO." He advises large companies on search strategy in an AI-driven environment. Follow him for a product-focused perspective on how to build content that AI engines surface. He outlines his four pillars of AI search on the AirOps webinar below.

Technical and measurement experts

These three experts focus on the technical side of AI search and how to measure results. Their work shows how LLMs retrieve information and what you can do to make your content easier for AI engines to cite.

Mike King is the founder and CEO of iPullRank. He coined "relevance engineering," a framework that fuses AI, content strategy, information retrieval, and digital PR. He was named Search Engine Land's AI Search Marketer of the Year (2025). Follow him for the most technical and forward-looking work in the GEO space. He explains how to reframe your search opportunity on the AirOps webinar below.

Lily Ray is VP of SEO & AI Search at Amsive and runs independent consulting through Algorythmic. She leads research on algorithm updates, E-E-A-T, and AI Overviews CTR. Follow her for rigorous analysis of how Google and AI engines evaluate content quality. She covers what recent algorithm updates mean for your strategy on the AirOps webinar below.

Crystal Carter is Head of AI Search and SEO Communications at Wix, informing AI search product strategy for 300M+ users. She leads AEO education across the Wix platform. Follow her for insight into how major platforms are adapting to AI search. She breaks down the difference between LLM visibility and SEO KPIs on the AirOps webinar below.

Who to follow by role and goal

Pick 2-3 experts to start based on your role. Trying to follow everyone leads to information overload. Focus on the experts whose specialty aligns with your day-to-day work, then expand your list once you have a baseline.

• If you focus on content, start with strategists who publish frameworks you can apply.
• If you need technical depth on relevance engineering and algorithm research, prioritize the technical and measurement specialists.
• If your job is proving ROI, look at the measurement-focused experts like Crystal Carter and Lily Ray.
• If you want to understand the broader shift in search behavior, start with Kevin Indig's research on ChatGPT versus Google.

How to act on what these experts teach

Following AI search experts is step one. The payoff is tracking whether your own brand gets cited in AI answers and then acting on what you learn.

The 2026 State of AI Search report from AirOps found that about 85% of brand mentions come from third-party sources, not owned content. Brands that build third-party mentions are 6.5x more likely to earn AI search visibility than through owned content alone. Only 30% of brands stay visible from one AI answer to the next.

These numbers point to a clear priority: track your AI visibility, then build the third-party signals that drive it. Your owned content matters, but third-party validation is what LLMs look for when deciding which brands to cite.

• Track citation rate: how often your owned pages are cited as sources in AI answers.
• Track mention rate: how often your brand name appears in AI responses.
• Monitor share of voice: how you compare to competitors in AI search results.
• Audit third-party mentions: identify which external sources mention you and where gaps exist.

You need AI visibility metrics to know if the strategies these experts teach are working for your brand. Dashboards that show you data are useful. Systems that connect insight to execution and track results over time are better. The AEO tools you choose should close the loop between what you learn and what you do about it.

Key takeaways

• AI search now shapes buyer discovery. The experts here help you stay visible where attention is moving.
• Credibility in AEO comes from published research, named frameworks, and documented results.
• Start with 2-3 experts whose specialty matches your role, then expand as your AI search strategy matures.
• Measurement closes the loop: track citations, mentions, and third-party signals to know what works.
• The LLM visibility practices these experts teach give you the foundation; tracking your results shows whether they work for your brand.

Frequently asked questions

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What is the difference between AEO, GEO, and SEO?

AEO (answer engine optimization) focuses on earning citations and mentions in AI-generated answers. GEO (generative engine optimization) describes strategies for surfacing content inside LLM responses. SEO (search engine optimization) targets rankings in traditional search results.

All three overlap. Strong SEO content often performs well in AEO. The difference is where you measure success: clicks for SEO, citations and mentions for AEO and GEO. Most teams now need to track both traditional rankings and LLM visibility to get a complete picture.

How can I tell if someone is a real AI search expert?

Look for published research, documented results, named frameworks, and peer recognition. Avoid anyone who only shares opinions without showing their work. Industry awards (like Search Engine Land's Marketer of the Year) and citations from other experts are strong signals. Check whether their advice has been tested and whether they acknowledge the limits of their knowledge.

Do I still need traditional SEO if I focus on AEO?

Yes. SEO and AEO reinforce each other. High-quality content that ranks in Google also tends to get cited in AI answers. The fundamentals (clear structure, accurate information, authoritative sources) apply to both. Ignoring SEO while chasing AEO would weaken your overall discoverability.

How do I know if my brand is being cited in AI answers?

Use an AI visibility platform that tracks citations and mentions across ChatGPT, Gemini, Perplexity, and other engines. Manual spot-checks are useful but do not scale. Dedicated tools show you citation rate, mention rate, and share of voice over time. This data helps you spot gaps and measure whether your optimization efforts are working.