AI Search Visibility
Your content is visible to humans. That doesn't mean it's visible to the AI models that now answer your buyers' questions before they ever visit your site.
Most marketing teams are optimizing for a search experience that's already changing underneath them. Traditional search engine optimization (SEO) assumes a human will click a link and read a page. Generative AI search doesn't work that way. The model fetches your page, parses what it can access, and either cites you or moves on. You don't get a second shot.
The problem is that marketers are flying blind. They're publishing content without knowing whether large language models (LLMs) can read it. They're crafting positioning statements that AI agents might never surface because the content is locked behind JavaScript rendering or buried in dynamic components.
Two tools fix that. Neither requires a large budget. Both reveal different parts of the same problem: not just whether AI can see your content, but whether your ideas register as worth citing.
The Visibility Problem Is Technical Before It's Strategic
When an AI system fetches a web page, it doesn't render the full browser experience. It reads a simpler version. JavaScript-heavy pages, content loaded asynchronously, and text buried in interactive components often don't make it into what the model processes. Your beautifully designed product page might look complete to a visitor and almost empty to the AI answering a prospect's question about your category.
This is the gap the Adobe LLM Optimizer Chrome extension was built to surface.
Tool One
Adobe AI Content Visibility Checker
Install the extension, navigate to any page on your site, and click it. The tool compares what a human visitor sees against what an AI agent can actually read, then returns a citation readability score. It highlights specific content that stays hidden from LLMs.
A low score on a core product page or a category landing page is a concrete problem with a concrete fix. It tells you whether the content you've invested in actually exists, from an AI's perspective.
Adobe's own team used the full LLM Optimizer platform to audit Adobe.com and found that product descriptions, ratings, and reviews weren't surfacing in AI responses. After addressing the visibility gaps, AI citations for Adobe Firefly increased substantially within one week (Adobe-supplied figure, unaudited).
The free Chrome extension does single-page diagnostics. The enterprise platform goes further, with site-wide auditing, competitive benchmarking, and one-click optimization deployment. For most marketing teams, the free extension is the right starting point.
Running the extension across your ten most strategically important pages takes under thirty minutes. What you find there tells you whether AI visibility belongs on your roadmap now or whether you have a crisis that's already underway.
Visibility Is Necessary. Being Cited Is Different.
Getting your content read by an AI system is the baseline. The real question is whether your ideas register as significant enough to surface in a generated response. That's a different problem, and it's where most B2B content fails.
Enterprise content tends to be thorough and carefully worded. It's also often indistinguishable from every other player in the category. When an AI model synthesizes a response about your market, it draws on what's genuinely novel or authoritative. Competent content that restates category consensus doesn't get cited. It gets absorbed and averaged out.
Getting your content read by an AI is the baseline. The real question is whether your ideas register as significant enough to surface.
What's Up With That? (WUWT) is a browser extension built by Marshall Kirkpatrick that addresses this directly. It applies structured analytical lenses to any article, PDF, or page you're reading, including your own drafts.
Tool Two
What's Up With That? (WUWT)
WUWT maps the current state of knowledge in a field, then assesses what's genuinely new in the content you're reading. It runs more than 35 analytical frameworks: argument mapping, blind spot identification, common sense critiques, expert panel simulation, causal loop analysis, and more.
The practical application for content marketers: run it on your own posts before you publish. If the "what's new here" analysis comes back thin, AI models will likely treat your piece the same way. If your key frameworks and positions come back as genuinely distinct signals, you have content that AI systems are more likely to surface when your category comes up.
Kirkpatrick built the tool solo over six months using Claude Code. It works on articles, research papers, PDFs, email newsletters, and YouTube videos. The free tier allows three page analyses per day.
Used together, these two tools answer the two questions that matter most for AI search visibility: Can the AI read my content? And if it can, does my content have anything worth saying?
This Is a Content Strategy Question, Not Just a Technical One
What the Adobe checker reveals about your site architecture is fixable by a web team. What WUWT reveals about your content is a harder conversation.
B2B marketing content has optimized for volume and keyword coverage for years. That strategy produced sites that were legible to Google's crawlers but often thin on original thinking. AI models are now the arbiters of what gets cited and what gets ignored, and they favor specificity and genuine insight over coverage.
If your content describes the category well but doesn't advance a distinct position, AI-generated summaries of your market will mention your competitors before they mention you. The tools that surface this early are valuable precisely because they make a diffuse problem concrete.
Run the Adobe checker today. You'll have a citation readability score within minutes. Then use WUWT on your three most important pieces of content. Treat the analysis as a content brief for everything you publish next.
What to Do on Monday
Three Actions This Week
- Install the Adobe AI Content Visibility Checker and run it on your homepage, your primary product or service page, and your highest-traffic blog post. Document the citation readability scores. If any score is below 70%, flag that page for technical review before your next content investment there.
- Install What's Up With That? and run your most recent published piece through it. Look specifically at what the tool identifies as novel versus what it flags as standard industry framing. That gap is your content brief.
- Brief your content team on the difference between content that covers a topic and content that advances a position. AI models cite the latter. Make that distinction explicit in your editorial standards before the next content calendar cycle.
Sources
- Adobe. "Evaluate your site's AI Search visibility with Adobe LLM Optimizer." Adobe Business Blog, 14 Nov. 2025, business.adobe.com.
- Adobe. "Media Alert: Adobe Delivers LLM Optimizer for Businesses to Boost Visibility Across AI-Powered Chat Services and Browsers." Adobe Newsroom, 14 Oct. 2025, news.adobe.com.
- Kirkpatrick, Marshall. "What's Up With That? — AI-Powered Reading Analysis." whatsupwiththat.app, 2026, whatsupwiththat.app.
- Lusher, Carter. "AR Intelligence: Live — Tool Talk with Marshall Kirkpatrick, What's Up With That?" Lusher Advisory, Apr. 2026, lusheradvisory.substack.com.
- Kirkpatrick, Marshall. "What's Up With That?" Product Hunt, 27 Feb. 2026, producthunt.com.