{"id":1194,"date":"2026-07-13T06:53:22","date_gmt":"2026-07-13T06:53:22","guid":{"rendered":"https:\/\/maxaeo.ai\/blog\/get-experts-cited-ai-search\/"},"modified":"2026-07-13T06:53:22","modified_gmt":"2026-07-13T06:53:22","slug":"get-experts-cited-ai-search","status":"publish","type":"post","link":"https:\/\/maxaeo.ai\/blog\/get-experts-cited-ai-search\/","title":{"rendered":"How to Get Experts Cited in AI Search: Expert Commentary and HARO-Style Sourcing"},"content":{"rendered":"

To get experts cited in AI search<\/strong>, you need AI engines to attribute a claim to a named person \u2014 "according to [Name], [title] at [company]" \u2014 not just to your domain. That means turning your in-house subject-matter experts into quotable, verifiable, well-sourced entities that ChatGPT, Perplexity, Google AI Overviews, and Copilot can recognize and reuse in generated answers.<\/p>\n

Most guides stop at the brand or domain level. This one works at the person level<\/strong> and closes a loop the others skip: how to actually measure whether your people get named. You'll get a repeatable framework, a quote-ready writing formula, the 2026 HARO-style sourcing landscape, and a per-engine cheat sheet \u2014 with every hard number tied to a named source.<\/p>\n

\"Dashboard<\/figure>\n

What does "get experts cited in AI search" mean?<\/h2>\n

It means an AI-generated answer names a specific individual \u2014 and often their role and employer \u2014 as the authority behind a claim, rather than only linking a website.<\/strong> A domain citation says "Source: acme.com." A person citation says "As Jane Lee, Head of Research at Acme, explains\u2026" The second is stickier: it travels across engines and follows the expert even when the URL changes.<\/p>\n

This matters because AI systems increasingly reward entity authority<\/strong> \u2014 how well an engine knows and trusts a named thing \u2014 over raw domain metrics. A person is an entity. When you make an expert legible to machines, you give the model a reusable, low-risk source to attach opinions and definitions to. That is the whole game.<\/p>\n

Why AI answers quote people, not just brands<\/h2>\n

AI engines prefer named humans because a person carries verifiable credentials, a track record, and cross-web corroboration that a faceless brand claim does not.<\/strong> "Jane Smith, epidemiologist" is easier to trust \u2014 and safer to quote \u2014 than "XYZ Marketing Corp says."<\/p>\n

The data backs the shift toward source-level trust. Ahrefs found that the majority of ChatGPT citations come from domains with a Domain Rating of 80\u2013100<\/strong>, and that AI systems show a recency bias toward fresher content (Ahrefs' analysis of LLM citations<\/a>). Semrush reports that Google triggered AI Overviews for 13.14% of U.S. desktop searches<\/strong> by March 2025 (up from 6.49% in January) and that 60% of Americans now use AI to find information at least sometimes<\/strong> (per an AP-NORC survey cited in Semrush's AI SEO research<\/a>).<\/p>\n

Translation: more answers are being generated, and they lean on high-trust sources. A recognized expert is a portable trust signal you own \u2014 the same entity logic that sits behind broader AI search visibility<\/a>.<\/p>\n

The Named-Expert Citation Loop: a five-step framework<\/h2>\n

Getting a person cited is not one tactic; it's a loop of five stages you repeat per expert, per topic.<\/strong> Run it end to end, measure, then feed results back into stage one.<\/p>\n

    \n
  1. Identify<\/strong> \u2014 Pick one expert and the 5\u201310 questions they should "own" in AI answers. Match the person to queries where their real experience is defensible.<\/li>\n
  2. Package<\/strong> \u2014 Create quote-ready material: a tight bio, verifiable credentials, an author byline, and blocks of text written to be lifted (formula below).<\/li>\n
  3. Place<\/strong> \u2014 Publish that material on owned pages and<\/em> earn it on third-party sites through expert commentary and HARO-style sourcing.<\/li>\n
  4. Entity-build<\/strong> \u2014 Make the person machine-legible: consistent name and title everywhere, author schema, LinkedIn, and ideally a knowledge-graph presence.<\/li>\n
  5. Measure<\/strong> \u2014 Track whether the name<\/em> appears in AI answers across engines, then return to step one with what worked.<\/li>\n<\/ol>\n

    The loop matters because a single placement rarely moves an engine. Repetition of the same person-claim across owned and earned surfaces<\/strong> is what teaches a model that the attribution is stable.<\/p>\n

    Make your expert "quote-ready"<\/h2>\n

    Quote-ready material is text an engine can extract as a self-contained, attributed claim without editing.<\/strong> If a model has to rewrite your sentence to make it usable, it will often grab a competitor's cleaner version instead.<\/p>\n

    The anatomy of a liftable quote is specific claim + evidence + attribution + mechanism. Compare:<\/p>\n\n\n\n\n\n\n\n\n
    Element<\/th>\nWeak version<\/th>\nQuote-ready version<\/th>\n<\/tr>\n<\/thead>\n
    Claim<\/td>\n"AI search is a big deal."<\/td>\n"AI answers increasingly name a person as the source, not just a URL."<\/td>\n<\/tr>\n
    Evidence<\/td>\n"Studies show this works."<\/td>\n"One site lifted its AI citations ~40% in 90 days after adding direct answers and original case-study data."<\/td>\n<\/tr>\n
    Attribution<\/td>\n"Experts say\u2026"<\/td>\n"says Jane Lee, Head of Research at Acme Analytics"<\/td>\n<\/tr>\n
    Mechanism<\/td>\n"It just works."<\/td>\n"because engines can attach a verifiable claim to a recognized entity"<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    That 40% figure is real: Baruch Labunski of Rank Secure reported a ~40% increase in brand citations in AI results within 90 days<\/strong> after adding direct answers and original case-study data \u2014 roughly 120 new pages plus ~15 revised, per Semrush's reporting<\/a>. Notice the format \u2014 a named person, a number, a timeframe. That is exactly the shape AI models like to reuse.<\/p>\n

    Practical rule:<\/strong> end every expert insight with the attribution attached, not floating three paragraphs away. Pair each quote with a visible byline and, where possible, author schema so an engine can trust who wrote it.<\/p>\n

    \"Example<\/figure>\n

    HARO-style sourcing in 2026: where experts earn quotes<\/h2>\n

    HARO-style sourcing means responding to journalist and publisher requests so your expert gets quoted in third-party articles \u2014 the earned mentions AI engines trust more than your own site.<\/strong> AI systems consistently pull citations from outside<\/em> brand-owned domains for comparative and evaluative queries, so where your expert appears matters as much as what your own pages say.<\/p>\n

    The landscape changed. The original HARO was rebranded as Connectively, which shut down; the HARO name was later acquired by Featured.com, and HARO founder Peter Shankman launched a successor, Source of Sources<\/strong>. Here are the platforms worth your experts' time, per BuzzStream's tested comparison of HARO alternatives<\/a>:<\/p>\n\n\n\n\n\n\n\n\n\n
    Platform<\/th>\nBest for<\/th>\nPricing<\/th>\n<\/tr>\n<\/thead>\n
    Source of Sources<\/td>\nHARO successor; broad daily requests<\/td>\nFree<\/td>\n<\/tr>\n
    Qwoted<\/td>\nTier-1 publisher placements<\/td>\n~$99\/mo Pro<\/td>\n<\/tr>\n
    Featured<\/td>\nCurated expert roundups for major publishers<\/td>\nVaries<\/td>\n<\/tr>\n
    Help a B2B Writer<\/td>\nB2B\/SaaS-specific requests<\/td>\nFree<\/td>\n<\/tr>\n
    Dot Star Media<\/td>\nReal-time X\/BlueSky alerts<\/td>\nFree (US)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Qwoted skews toward tier-1 outlets, which maps directly onto the high-DR sources AI engines favor \u2014 so a placement there does double duty. Feeding that earned coverage back into your owned content is the core of digital PR built for AI search<\/a>.<\/p>\n

    How to respond so you actually get picked<\/h3>\n

    Win rate on these platforms is a function of speed, specificity, and authenticity \u2014 in that order.<\/strong> Follow this sequence:<\/p>\n

      \n
    1. Respond within the first hour.<\/strong> Journalists work on deadline; the first strong, usable quote often wins.<\/li>\n
    2. Answer the exact question asked<\/strong> \u2014 no generic boilerplate, no pivot to a sales pitch.<\/li>\n
    3. Lead with a number or a first-hand example<\/strong> the reporter can't get elsewhere.<\/li>\n
    4. Attach a one-line bio and credentials<\/strong> so the byline writes itself.<\/li>\n
    5. Never send AI-generated pitches.<\/strong> As Source of Sources founder Peter Shankman puts it: "DON'T use AI. We can always tell, and it'll always be terrible." Detectable AI copy gets you skipped and can burn the relationship.<\/li>\n<\/ol>\n

      Build the expert as an entity AI recognizes<\/h2>\n

      An expert becomes a machine-readable entity when their name, title, and expertise are consistent and corroborated across the open web.<\/strong> Inconsistency \u2014 "J. Lee" here, "Jane Lee, PhD" there, a different employer on LinkedIn \u2014 fragments the signal and makes engines hesitant to attribute.<\/p>\n

      Do three things:<\/p>\n