10 Experts on AI Search in 2026

Fishkin has argued consistently through 2024 and 2025 that the open web's over-reliance on Google is a structural risk, and that AI search is accelerating a long-overdue diversification. His writing and talks at SparkToro push brands to measure audience reach across multiple platforms — Reddit, YouTube, podcasts, Substack, LinkedIn — rather than chasing the shrinking Google click. In the citation economy, that multi-channel presence doubles as raw material for what LLMs quote.

Solís has written and spoken extensively through 2025 about the need to optimize for LLM citation as a first-class objective, not a downstream side-effect of classic SEO. Her newsletter and conference talks emphasize passage-level structure, structured data, and the E-E-A-T signals that LLMs measurably reward. She is one of the most referenced voices on what she terms the move from “search engine optimization” to “answer engine optimization.”

Ray's 2024–2025 research on Google core updates extended cleanly into the AIO era. She has repeatedly demonstrated that the sites gaining share in AIOs are the ones that already score highest on Google's E-E-A-T signals — real authors, transparent expertise, and demonstrable first-hand experience. Her position, laid out across Search Engine Land and her own X account, is that the new ranking factors are the old ranking factors, applied more strictly.

Schwartz's daily reporting on Search Engine Roundtable is the closest thing the industry has to a system of record for Google volatility, AIO rollout, and feature changes. His recent writing has tracked the expansion of AI Overviews from 13% to ~25% of queries with week-by-week precision, as well as the live deployment of features like AI Mode and the slow tightening of Google's acceptable-content thresholds.

Indig has written extensively in 2025 about what he calls “the Great Decoupling” — the separation of Google rankings from traffic, and of traffic from revenue. His newsletter has documented specific case studies of brands earning LLM citations through structured data, community presence, and original first-party data, even when their classic Google traffic is flat or declining.

Schwartz's long-running argument — that the most defensible SEO strategy is to build pages that are genuinely useful as products, not just optimized as content — has aged exceptionally well into the AI search era. His writing in 2025 made the case that programmatic and tool-driven pages (calculators, comparison engines, search experiences) are harder for LLMs to substitute for, and therefore generate disproportionate citations and referral traffic.

Shepard's 2025 research at Zyppy has focused on the enduring importance of backlinks and site-wide technical health as prerequisites for ranking and, downstream, for LLM citation. His position, stated repeatedly in talks and Zyppy research posts, is that authority signals have if anything become more important in the AI era — because LLMs overwhelmingly cite from high-authority domains.

Haynes has become the industry's most cited voice on Google's Quality Rater Guidelines and E-E-A-T, and her 2024–2025 writing has extended those frameworks directly into the AIO and LLM citation context. She has argued that sites that invest in real named experts, transparent methodology, and author-level authority are accruing citations at a multiple of less transparent competitors — a position supported by the citation data now emerging from seoClarity and Semrush.

Capper's ongoing work at Moz on SERP volatility and ranking factor analysis has become one of the few sources of peer-level rigor on what actually changed in 2025. His 2025 research highlighted the compounding effect of AIO rollout on organic CTR patterns across query types, and made the case that tracking position-1 CTR has become more informative than tracking ranking position alone in the AI era.

Muller has been one of the earliest and clearest voices bridging the gap between data science and SEO. Her 2024–2025 writing and talks have focused on giving marketers practical tools to measure LLM citation patterns, fine-tune prompts for content optimization, and instrument their own sites against the new AI-referral traffic sources. She emphasizes that the SEOs who win 2026 are the ones comfortable with Python notebooks, embeddings, and citation tracking — not just GSC.