Kaleigh Moore’s AEO play

Kaleigh Moore is pitching a new playbook for the artificial-intelligence search era: brands should track the signals that get them cited by chatbots, not just the links that get them ranked. (pr.com) Moore, an Austin-based answer-engine optimization strategist, introduced the “Source Signal Stack” on April 23 as a four-layer framework for why business-to-business companies can rank in Google and still miss citations in ChatGPT, Perplexity, Claude, and Google AI Mode. Her release says the layers run from brand-owned properties to executives, non-executive subject-matter experts, and outside validation. (pr.com) Two days earlier, Moore laid out the same idea on her own site and argued that employee posts on LinkedIn should sit inside the same program as answer-engine optimization, not beside it. She wrote that product managers, solutions engineers, and customer-success leaders publishing under their own names can help make a company “citable” in artificial-intelligence answers. (kaleighmoore.com) Answer-engine optimization is the business of getting an artificial-intelligence system to quote or cite your material when it answers a question. Search Engine Land described the shift this year as moving from “10 blue links” to the two-to-seven domains that large language models tend to cite in a single response. (searchengineland.com) The data Moore cites reflects that shift away from classic rankings. Moz said in February that 88% of Google AI Mode citations were not in the organic search results for the exact-match query, and AirOps said in its 2026 state-of-search report that 85% of brand mentions in artificial-intelligence responses came from third-party pages rather than owned domains. (moz.com) (airops.com) Her framework leans heavily on LinkedIn because recent studies have found the platform rising fast as a citation source for professional topics. Profound said last month that LinkedIn became the No. 1 most-cited domain for professional queries across major artificial-intelligence search platforms, while Semrush said last month it analyzed 89,000 cited LinkedIn URLs across 325,000 prompts. (tryprofound.com) (semrush.com) Moore’s argument is narrower than a general search-engine-optimization update. She is telling business-to-business brands that a company blog and a chief executive’s profile are often too “top-heavy” for systems that cross-check identity, expertise, and third-party mentions before deciding what to cite. (pr.com) That puts her release inside a fast-growing market for artificial-intelligence visibility services. PR Newswire published its own answer-engine optimization and generative-engine optimization report on April 6, and AirOps rolled out an “Offsite” product in February built around third-party visibility beyond a brand’s own site. (prnewswire.com) (financialcontent.com) The hard part is that most of the evidence behind these tactics comes from vendors, agencies, and consultants selling the work. Moore’s framework is a diagnostic model and not an independent study, but it captures where marketing budgets are moving as artificial-intelligence answers send attention to cited sources instead of ranked pages. (pr.com) (searchengineland.com)