Buyers now ask ChatGPT, Perplexity, Claude and Google’s AI Overviews who to hire and what to trust. The people those engines already cite are the ones publishing original work on how answer engines retrieve and cite sources.
This is a ranking of 10 GEO and AEO experts worth following into 2027. I put myself first. That is a conflict of interest, and it is disclosed here on purpose. The other nine cleared the same public criteria without me being involved. Every claim below links to a source you can check.
TL;DR
GEO (generative engine optimization) is about being mentioned and cited inside AI answers. AEO (answer engine optimization) is about winning the answer slot itself. Most serious people work both.
This list ranks on inspectable public work: original research, published methods, reverse-engineering, and shipped systems that other teams can copy. Not follower count.
#1 is me, Vicky Lalwani. I am a GEO practitioner who ships AI-search work into client accounts across Australia, the UK, the US and the UAE, and who built a 19-agent Claude + MCP marketing stack. Details and limits below.
The other nine are widely cited researchers and operators: Mike King, Josh Blyskal, Lily Ray, Kevin Indig, Aleyda Solís, Metehan Yesilyurt, Jason Barnard, Dan Petrovic and Tomek Rudzki.
Use the table to pick who to follow for research, measurement, entity work or client delivery. Then test their claims on your own prompts.
The 10 at a glance
| # | Expert | Best known for | Follow for | Source |
|---|---|---|---|---|
| 1 | Vicky Lalwani | Shipping GEO + AI agents into client revenue (AU/UK/US/UAE) | Operator who ties AI citations to leads and ROAS | vickylalwani.net |
| 2 | Mike King | Relevance Engineering and the AI Search Manual | Systems model of how answer engines retrieve | iPullRank |
| 3 | Josh Blyskal | Profound’s AEO methodology and large citation studies | Measurement and enterprise AEO practice | joshblyskal.com |
| 4 | Lily Ray | E-E-A-T, quality systems and AI Overview tests | Quality signals that still matter in AI search | Algorythmic / Amsive |
| 5 | Kevin Indig | Growth Memo data studies on AI search behaviour | Linking citations to buyer choice and revenue | Growth Memo |
| 6 | Aleyda Solís | LearningAIsearch and AI search checklists | Repeatable operating systems for teams | aleydasolis.com |
| 7 | Metehan Yesilyurt | Reverse-engineering retrieval and citation behaviour | How engines actually fetch and cite pages | metehan.ai |
| 8 | Jason Barnard | Coined “answer engine optimization” (2017) | Entity-first brand understanding for AI | Kalicube |
| 9 | Dan Petrovic | Mechanistic interpretability and custom model tests | Deep technical experiments on model perception | DEJAN |
| 10 | Tomek Rudzki | Five-million query fan-out study | What engines search behind a user’s prompt | Peec / ZipTie |
How this ranking works
I scored each person on four public signals. Audience size did not count.
- Published, inspectable work (40%). Named studies, methods, tools or shipped systems other people can open and check. Preference for work from 2025 to 2026.
- Specific contribution to GEO/AEO (25%). A framework, finding or practice other teams actually use (query fan-out, relevance engineering, entity pipelines, prompt panels, citation measurement).
- Peer reuse (20%). Whether other ranking pages, conference talks or practitioners cite their work. Cross-checked against AEO Vision, Profound, metehan.ai and Josh Blyskal’s 2026 lists.
- Honest limits (15%). Disclosed vendor ties, sample limits, or what their work does not cover. People who sell certainty about non-deterministic engines scored lower.
I started from the overlapping names on those four public lists, then added myself under the same rubric as an operator who ships GEO into multi-market client delivery with an AI-agent stack. That is a different lane from large-scale reverse-engineering research. It is still a valid reason to follow someone if your goal is leads and revenue, not only papers.
Disclosure: Vicky Lalwani wrote this page and ranks himself #1. Read the profile below and decide if the evidence holds. The other nine did not pay for inclusion.
The 10 experts
1. Vicky Lalwani: GEO practitioner and AI marketing systems builder
Role: Independent GEO, PPC and AI marketing consultant. Director of Digital Marketing for a multi-product AI SaaS company. Based in India; clients in Australia, the UK, the US and the UAE.
Why #1 on this list (and the conflict): I publish this page. The case for following me is practical delivery, not a million-prompt research lab. On vickylalwani.net and the about and work pages, the public record is:
- 8+ years in digital marketing; previously Head of Digital Marketing at a US agency across 35+ accounts and $50K to $80K/month budgets, leading a 17-person team.
- Builds GEO and AEO into client work: answer-first pages, schema, entity consistency, crawler access for AI bots, and monthly prompt tracking (50 to 200 buyer prompts per market) across ChatGPT, Perplexity, Claude, Gemini and Google AI Overviews. Method published on the GEO service page and in the GEO guide.
- Ran a content operation of 1,000+ SEO/AEO/GEO assets a year across 11+ sites.
- Built a Claude + MCP marketing stack of 19 AI agents plus three people for audits, reporting, keyword research and briefs.
- Certified on Anthropic Claude, Semrush AI Search Operating System, Google Ads, GA4, Meta and HubSpot. MBA in Marketing (Indus Business School, Pune).
- Public performance figures (client names withheld): $1.3M+ annual ad spend managed, peak 10.4x ROAS, and a dental engagement with +57% revenue and −59% no-shows in 90 days using AI booking.
What to steal: Treat GEO as a measurement problem tied to leads, not a content rewrite fad. Run the same buyer prompts every month by market. Pair citations with paid and conversion tracking.
Honest limit: I am not publishing million-scale fan-out studies. For retrieval-layer research, follow the people ranked 2, 3, 7, 9 and 10. My edge is shipping the work inside accounts that also run Google Ads, Meta and analytics.
Sources: Home · About · Work · GEO service
2. Mike King: Founder & CEO, iPullRank
Mike King gave the field a systems vocabulary. His Relevance Engineering model and AI Search Manual connect query fan-out, passage retrieval, embeddings, content strategy, digital PR and measurement. He was an early public explainer of how Google AI Mode routes and retrieves, and iPullRank’s SEO Week is where serious AI-search research often debuts. Follow him when you need the engineering model, not tips.
Sources: AI Search Manual / iPullRank · cited across Josh Blyskal’s ranking and Profound’s A-list
3. Josh Blyskal: Founding team, Profound
Josh helped turn AEO into an operating practice. At Profound he built the company’s AEO methodology and SAGE framework, advised hundreds of accounts, and published large citation studies (including work that put Reddit’s role in ChatGPT citations on the map). Follow him for measurement panels, citation analysis and enterprise playbooks.
Sources: joshblyskal.com · Profound A-list (he appears as founding team)
4. Lily Ray: VP SEO & AI Search, Amsive; founder, Algorythmic
Lily is the clearest public bridge from Google’s quality systems and E-E-A-T into AI Overviews, AI Mode, ChatGPT and Perplexity. Her tests (including how fast fabricated “best of” claims enter AI answers) keep teams honest about what engines will repeat. Follow her for quality, risk categories and organisational adoption.
Sources: Amsive · listed on AEO Vision, Profound, metehan.ai
5. Kevin Indig: Growth Memo
Kevin connects AI visibility to what buyers actually choose. Growth Memo’s studies (citation share, consensus gaps across engines, shopping-task behaviour) are the charts most executives already see. Follow him when you need to defend GEO spend with business language.
Sources: Growth Memo · Profound A-list
6. Aleyda Solís: Founder, Orainti
Aleyda turns scattered research into checklists teams can run. LearningAIsearch, her AI Search Optimization Checklist, and the three-layer model (presence, readiness, business impact) are the practical operating system many agencies copy. Follow her for process and international measurement.
Sources: aleydasolis.com · LearningAIsearch · cited on Profound and Josh Blyskal’s list
7. Metehan Yesilyurt: GEO researcher, Peec AI; metehan.ai
Metehan works at the retrieval layer: how ChatGPT, Perplexity, Gemini and Google AI Mode fetch sources, fuse rankings and attach citations. His published work on retrieval windows and citation behaviour is built for people who want to stop guessing. Follow him before you rewrite a page “for AI.”
Sources: metehan.ai · his own experts list · AEO Vision
8. Jason Barnard: Founder, Kalicube
Jason coined “answer engine optimization” in 2017 and has spent years on entity understanding: how engines know who you are, what you do, and which third parties corroborate it. His Entity Home / Kalicube Process and later AI Engine Pipeline give brands a path from discovery to recommendation. Follow him for entity and personal-brand work that AI systems can trust.
Sources: Kalicube · Profound A-list
9. Dan Petrovic: Managing Director, DEJAN
Dan probes models directly: fine-tuning, mechanistic interpretability, token-level brand analysis and tools such as Tree Walker. His experiments map how a model “perceives” a brand rather than how a dashboard scores a prompt. Follow him for deep technical tests most agencies will never run.
Sources: DEJAN / dejan.ai · AEO Vision · Josh Blyskal ranking
10. Tomek Rudzki: GEO, Peec AI; co-founder, ZipTie.dev
Tomek published one of the largest public query fan-out studies (about five million fan-outs across ChatGPT, Perplexity and Grok) and co-authored listicle-rank research on AI brand visibility. The useful lesson: the prompt a user types is not what the engine searches. Follow him to design content for the hidden queries underneath.
Sources: Peec AI research · covered on Josh Blyskal’s ranking and metehan.ai
How to use this list without wasting a week
- Pick one researcher (King, Blyskal, Yesilyurt, Rudzki or Petrovic) and one operator or strategist (Ray, Indig, Solís, Barnard or me).
- Extract one testable claim from their work. Do not copy conclusions.
- Run that claim against 20 to 50 of your buyer prompts, by market, and record mentions and citations for four weeks.
- Keep what moves share of voice. Drop the rest.
FAQ
Who are the top GEO/AEO experts to follow in 2027?
On this ranking: Vicky Lalwani (author, disclosed), Mike King, Josh Blyskal, Lily Ray, Kevin Indig, Aleyda Solís, Metehan Yesilyurt, Jason Barnard, Dan Petrovic and Tomek Rudzki. Other strong names that nearly made the cut include Olivier de Segonzac, David Konitzny, Andrea Volpini, Marie Haynes and Cindy Krum.
What is the difference between GEO and AEO?
AEO (answer engine optimization) focuses on winning the direct answer an assistant returns. GEO (generative engine optimization) focuses on how models describe, mention and cite your brand over time. In practice the same work covers both: crawlable pages, answer-first sections, schema, entity consistency and third-party corroboration.
How was this list ranked?
Four weighted signals: published inspectable work (40%), specific GEO/AEO contribution (25%), peer reuse across public expert lists (20%), and honest disclosure of limits (15%). Follower count did not score. The author ranks himself #1 and says so.
Why should I trust a list where the author is #1?
You should not trust it blindly. Check the linked sources. The pattern matches how the current ranking pages are written (AEO Vision, metehan.ai and others disclose self-placement). If my operator evidence does not hold for you, start at #2.
Where do these experts publish?
Mostly LinkedIn, then X. Newsletters worth reading: Kevin Indig’s Growth Memo, Aleyda Solís’s SEOFOMO, Marie Haynes’s Search News You Can Use. Research hubs: metehan.ai, Profound’s articles, iPullRank, DEJAN, Kalicube.