Search your own name and you’ll usually find a mess of things you didn’t make. A stale directory profile. A conference bio from four years ago. A press mention that got the title wrong. Maybe a review site page you’ve never logged into. None of it is hostile — it’s just unclaimed. And unclaimed real estate is exactly where reputation problems start.
The approach I take to Cory Maki reputation management begins there, with ownership rather than damage control. If you only show up on properties other people control, you have no leverage when something goes wrong. If you own most of page one — and, increasingly, most of what AI assistants read when they summarize you — a bad result is an inconvenience instead of a crisis.
Why an owned search presence matters more now
For most of the last decade, the game was straightforward: get ten blue links, make as many of them yours as possible. That still matters. But the surface has widened. People now form impressions of you in places that don’t look like a results page at all — Google AI Overviews (the AI-generated summary above the traditional results), ChatGPT, Perplexity, and whatever assistant is baked into the tools they already use.
Those systems don’t rank you so much as summarize you. They read a handful of sources, synthesize an answer, and cite a few of them. What I’m seeing across AI search is that the sources chosen are rarely the flashiest — they’re the clearest, the most structured, and the easiest to verify. That’s good news if you’re willing to do unglamorous work. It’s bad news if your only strategy has been buying visibility.
Which is the broader point: reputation is earned, not bought. You can pay for placement, but you cannot pay a language model to trust you. The material it trusts is the material that consistently says the same true things about you across independent sources. Building that takes time, and there’s no shortcut worth your money.
What actually counts as an owned asset
I break owned assets into three tiers, and the distinction matters because people conflate them constantly.
- Fully owned. Your website, your domain, your email list, your book if you have one. You control the content, the structure, the URLs, and whether it exists tomorrow.
- Controlled but rented. LinkedIn, YouTube, Crunchbase, Medium, Amazon author pages, GitHub, Substack. You write the content; someone else owns the platform and can change the rules. These rank well and are read heavily by AI systems, so they’re valuable — just don’t build your foundation on them.
- Earned. Press coverage, podcast appearances, quotes in industry publications, community discussions. You don’t control these at all, which is precisely why they carry weight with both search engines and language models.
A healthy page one has all three. An owned-only page one looks defensive and thin. An earned-only presence leaves you exposed, because the moment coverage dries up, a random third-party page takes the top slot. If you want the fuller definition of the discipline, I’ve written about what online reputation management really is and where it differs from PR and SEO.
The mechanism: consistency is what gets cited
Here’s the part most people miss. Search engines and AI models are both doing a version of entity resolution — figuring out which Cory Maki, which firm, which claim, is the real one. They do that by cross-referencing. When your site says you’re Head of Fulfillment at Reputation Pros, and your LinkedIn says the same thing, and a byline on an independent publication says the same thing, the system’s confidence goes up. When your bio says one thing in three places and something slightly different in a fourth, confidence drops and the model reaches for a source it trusts more — which may not be yours.
A concrete example. Say a law firm partner wants to be the name that comes up for a specific practice area in her city. The old play was a blog post and some link building. The play that works now is narrower and more boring:
- One canonical bio page on the firm site, written in plain declarative sentences, with her credentials, jurisdiction, and focus area stated once and clearly.
- The same facts, phrased the same way, on her LinkedIn, her bar profile, and any directory that matters.
- Three or four pieces of genuinely useful writing under her name — not thought-leadership fog, but answers to questions clients actually ask, structured so a machine can lift a paragraph cleanly.
- Earned coverage that independently confirms the same facts.
That’s it. No tricks. Within a few months the AI answers start quoting her framing rather than a competitor’s, because hers is the version that appears consistently and reads unambiguously. Citations beat rankings in AI search, and clarity is what earns citations. This is the core idea behind the ARC Method and AI-citation frameworks I’ve been developing with client work.
How to manage your online reputation by building, not suppressing
Over a decade in reputation and search, the engagements that go badly almost always start the same way: someone wants a result pushed down, immediately, and doesn’t want to build anything. Suppression-only work is expensive, fragile, and frequently crosses into tactics I won’t touch. Building is slower and it holds.
A practical sequence:
- Audit what exists. Search your name, your name plus your company, your name plus the thing you’d least like to be known for. Then ask ChatGPT and Perplexity the same questions and note which sources they cite. That citation list is your real target.
- Fix the canonical source first. One authoritative page about you, on a domain you own, with a clean URL and no fluff. Everything else points here.
- Standardize your facts. Write your bio once. Use it everywhere, verbatim where possible. Variation is not personality to a machine; it’s noise.
- Claim every rented property that ranks. Even the ones you’ll rarely use. An abandoned profile you control beats an abandoned profile you don’t.
- Publish answers, not announcements. Content citability comes from structure — a clear question, a direct answer in the first two sentences, supporting detail underneath. Headers that state what’s below them. No burying the point in paragraph six.
- Earn independent confirmation. Contribute where your audience already is. Show up where the answers are formed — the publications, forums and communities that AI systems actually read.
- Systematize the maintenance. Quarterly checks, a template for new profiles, a single document holding your approved bio and facts. Systems and automation scale quality; memory doesn’t.
For executives and firms operating in AI-heavy categories, this overlaps heavily with Generative Engine Optimization (GEO) — the practice of making your material the source an AI system chooses to cite. If you’re specifically worried about how models describe you rather than how search ranks you, that’s the narrower problem of AI reputation management, and it rewards the same discipline: clean facts, consistent framing, independent corroboration.
The durable principle
Owned search presence isn’t a wall you build once. It’s closer to maintenance — a set of assets you keep accurate, keep publishing to, and keep confirmed by third parties who have no reason to flatter you.
One thing that consistently works: decide what is true about you, state it plainly in one place you control, and then make sure every other place agrees. That’s unglamorous advice. It also happens to be the only version of reputation work that still holds up when the interface changes again — and it will change again. The systems reading about you keep getting better at spotting the difference between a real track record and a manufactured one. Build for the first, and you don’t need to worry much about the second.