AI Visibility Has a Language Problem

Jul 28

3 min read

Right now, ChatGPT is telling someone a nonprofit shut down in 2019. It didn't.

Welcome to AI visibility: a real problem buried under just enough jargon to make us all annoyed. SEO. GEO. AEO. LLMO. RAG. Schema. Zero-click search. Nobody has time for this.

So let's cut through it. You don't need to know what LLMO stands for. You need to know three things:

1. Is AI getting us right?

2. Are we showing up when it matters?

3. And if not, what do we fix first?

Here's your actual problem: you have too little time and too much to do. You're not losing sleep over whether your content is "optimized for generative retrieval." You're losing sleep because you've got twelve priorities, three of them are on fire, and now apparently ChatGPT is also out here describing your work like a game of telephone.

That's the problem Cited & Seen exists to solve. Not to make you fluent in jargon. To make sure AI describes your organization the way you'd describe it yourself, without you having to become an SEO expert (or even hire one) to get there.

Old search asked: do we rank? AI search asks a harder question: are we being understood?

An AI-generated answer might be the entire interaction someone has with your organization before deciding whether to visit, trust, recommend, or scroll right past you.

That means AI can get you wrong in more interesting ways than just "invisible." It can:

Summarize you inaccurately
Cite a source that's stale or thin
Skip the one program that actually matters
Mix you up with an organization down the street
Describe you in language so vague it says nothing
Leave you out of the conversation entirely

None of that is because your organization isn't doing great work. It's usually because the great work is scattered across six PDFs, four page versions, and one homepage that reads like it was written by committee. Which, let's be honest, it probably was.

Why smart organizations still get this wrong

You'd think the orgs doing the most credible work would be easiest for AI to understand. Often it's the opposite.

Insider language that means nothing outside your building. Program names that made sense in a 2018 strategic plan and nowhere else since. Key facts trapped in a PDF nobody's opened since the Obama administration (ahh miss those days). Five different explanations of the same initiative because nobody consolidated them. A homepage that sounds inspiring and explains nothing.

Clearly it's not a competence problem. It's a clarity problem. And clarity, annoyingly, is not most people's forte.

To be clear, here's what matters - no jargon required:

You don't need every acronym. You need to know where AI is pulling its information from, where your own story contradicts itself, what's most likely to get misread, and what to fix first. Four questions. Not forty.

Less "become an expert in generative engine optimization." More "hand me the mess, I'll hand you back a plan, go put out the fire that's on your desk."

Explore the AI Visibility Glossary The free Starter Guide is built for people with too much to do and no bandwidth to learn a whole new language.

When you want the full picture without doing the digging yourself, the AI Visibility Action Plan shows you exactly where AI gets you right, where it gets you wrong, and what to fix first.

Book a Call to talk through the Action Plan. When you book a call, you get the Cited, Seen, or Skipped? AI Accuracy and Authority for Mission-Driven Organizations, 173 page playbook for FREE!