There's a take making the rounds on Reddit and LinkedIn that goes about like this. AEO is a con. You can't track citations from a language model, the output is probabilistic, the model won't tell you why it picked anyone, so no amount of optimization work can move your visibility. A lot of them have done SEO for fifteen+ years and they're watching a fresh acronym get sold to clients with the confidence of a timeshare pitch. I get the reflex and they aren't fools for thinking that way.

Two Christmases running, Coca-Cola rebuilt its old "Holidays Are Coming" ad almost entirely with generative AI. The first attempt, in 2024, got called soulless and creepy within hours of going up. McDonald's tried its own AI Christmas spot in 2025 and pulled it within days after people savaged it. The footage in both was clean enough, the production cost was a rounding error next to a real shoot, and the brands had every rational reason to do what they did, but people unanimously hated it anyway. What bothered people had nothing to do with a glitchy hand or an extra finger. The ad felt made by nobody, for nobody, and watching it felt like a small insult.

I went through my own referrer log for the last 30 days and counted the AI-source visits. The picture isn't what the dashboards show. Here's what Claude.ai, Perplexity, NotebookLM, and a newsletter blast taught me about measuring AI search visibility in 2026.

New York's new AI disclosure law (S.8420-A) takes effect June 9, 2026. The compliance story has been covered. The bigger question for marketers is what happens to AI search visibility when "AI-generated" labels enter the visual web at scale.

I watched the Sundar Pichai keynote yesterday morning expecting the usual rhythm. A few model benchmarks, a couple of consumer demos, some developer plumbing, and maybe one feature that would matter for marketers in around eighteen months. That’s been the pattern at Google I/O for a decade, and you take notes, write a quick reaction, and move on. This time, it didn’t fit that pattern at all.

A consulting client walked me through her marketing operation a few weeks ago, and somewhere around minute twenty I realized I was looking at a list of every AI tool that’s been written up in Marketing Week since 2024. The AI-assisted content platform was in there, along with the lead-scoring add-on for the CRM and the new agentic follow-up tool that everybody on LinkedIn keeps posting case studies about. She had the budget for all of it, the team had the training, and her pipeline number was no different than it was eighteen months ago. It’s the same conversation I’ve been having with five other clients this year, which is why I finally decided to write about it.

ChatGPT brand citations dropped 41% in February and came back to 90% by late March. The volume recovered, but the list of who gets cited did not. Why the standard reading of the data is wrong, and what to do about it this quarter.

When you ask ChatGPT or Perplexity a question, how much of the answer is shaped by what the model knows about you? Here's what personalization actually does.

A scam text led me to a fake Oklahoma DPS page. I opened DevTools and found a phishing kit running tighter marketing measurement than most eight-figure programs. Here is what it teaches marketers about the AI search era.

Adobe finished buying Semrush this week and slipped a new acronym into the press release: ASO, agentic search optimization. The shift is real. The framing is partly marketing. Here's the honest read on what's new, what isn't, and what to add to your work if you've already been doing GEO. With sources, numbers, and a six-item readiness checklist.

In March, Ahrefs published an updated study of 863,000 keyword SERPs and roughly 4 million AI Overview URLs. The headline finding? Only 38% of pages cited in Google’s AI Overviews also appeared in the top 10 organic results for that same query. Seven months earlier, the same study had pegged that overlap at 76%.

A separate BrightEdge analysis put the overlap even lower, somewhere around 17%. Methodology differs across the studies, so I wouldn’t bet the house on any single percentage, but the studies all point the same direction, which is what I care about.

ChatGPT's GPT-5.3 and GPT-5.4 cite 93% different sources on the same prompts. If you're measuring AI visibility as one number, you're averaging two different models and missing the real brand signal. Here's what changed and what to do.

I ran the same six project management queries through ChatGPT, Perplexity, Gemini, and Google AI Mode on a single afternoon. Twenty-three responses, coded for every brand recommendation and every citation. The shortlist was more stable than I expected; the platforms were more different than I thought possible. Only one brand (Jira) was recommended by every platform on dev-team queries. ChatGPT pulled 73.7% of its citations from review sites; Google AI Mode pulled 40% from YouTube and Reddit. Thirteen brands exist on only one platform and are invisible everywhere else. And Gemini openly personalized its answers based on my Google account, referencing my actual team structure and business context by name. The industry talks about AI search as if it's one thing. Here's the data that says it's four things, each one pulling from a completely different universe of sources.

The industry keeps measuring AI search success with AI referral traffic, and the 2026 data says that ruler is shrinking. Similarweb shows US AI referrals dropped 15% in a single quarter while AI platform usage grew nearly 29%. Here are four myths about AEO and GEO that the data no longer supports, and what to track instead.

AI agent queries have hit 88% of human search volume, and 80% of the URLs that LLMs cite don't rank in Google's top 100. The old playbook isn't just underperforming; it's optimizing for the wrong game. Here's what 30 million citations tell us about what actually drives AI visibility in 2026, and what to do about it this quarter.

Pew Research found that users click traditional search results only 8% of the time when an AI summary appears. With AI Overviews now triggering on 48% of queries, brand visibility inside AI answers has become the most important metric in marketing. Here's what the 2026 data says and what to do about it.

Only 30% of brands persist from one AI-generated answer to the next, and 60% of AI Overview citations come from pages outside the top 20 organic results. The old SEO playbook has a blind spot. Here's what the 2026 data says about brand visibility in AI search, and the specific actions that actually move the needle.

The marketing teams that will define the next decade aren't the ones that adopted AI first. They're the ones that figured out what to protect before automating.

Microsoft just shipped a tool that shows you exactly which of your pages AI is citing and which queries are pulling them in. It's the first real transparency we've gotten from any major search platform, and what the data reveals about AI citation patterns is both promising and uncomfortable for most brands.