CLEARWATER, Fla. — Oct. 3, 2026 — Rob Tindula, writing in MarTech on 1 October 2026, set seven claims about AI search against data. The column’s list is: AI is killing traditional search; organic traffic cannot grow in a zero-click environment; purely AI-generated content cannot rank; llms.txt will help AI visibility; large language models have no trouble with JavaScript; AI is not driving much traffic; and SEO teams can be replaced by AI.
On the first, Tindula cites a State of Search report for the second quarter of 2026 that found AI search and traditional search growing at about the same rate quarter to quarter. He also writes that search demand is growing even while Google answers more queries itself and sends fewer clicks to the open web. On zero-click, he says the pressure is real and uneven, and he points to a local business that recorded its highest month of organic clicks in July 2026 from non-branded work.
On AI-written pages, the column says search engines are not running a penalty for whether a model wrote the page. They are filtering for whether the page adds anything. He points to four AI-generated articles, published between March and September of the prior year with light human review, that were still ranking. On llms.txt, he cites a 90-day look at ten sites before and after the file was added: most saw no measurable change in AI crawl frequency or AI-referred traffic. He reports Google’s position that it does not use llms.txt for AI-search discovery.
On JavaScript, he cites Profound’s finding that emerging AI-search providers do not render JavaScript, so server-side HTML is what they can read. On traffic, he cites an AI-mention study: after an assistant names a brand, that user’s visits to the brand site ran about 1.5 to 2.5 times a forecast baseline over the next seven days, while only about 2.5 percent of the downstream visits carried a trackable AI-referral parameter. About 20.5 percent of those visits came within an hour, 42 percent within a day, and the majority after the first day. His point is that referral reports undercount the visits. On replacing SEO teams, he cites an NP Digital study that found AI catching more errors while missing critical ones and struggling to rank what matters.
What the column does not settle
None of the seven myths is a test of whether two businesses with similar names have been resolved to the right website, phone, and legal entity. A page can pass every myth and still be the wrong firm. AI Verified did not rerun Tindula’s sources. The figures above are his column’s, and they stay there.
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Read the source: 7 AI search myths busted by data (Rob Tindula, MarTech, 1 October 2026).