In a recent LinkedIn post, Rand Fishkin expresses skepticism regarding the emerging trend of “AI Visibility” metrics, particularly concerning their impact on website traffic and business strategy. Fishkin, a prominent figure in the marketing and SEO community, challenges the assumptions underpinning these new metrics, suggesting they may not accurately reflect real-world user behavior or provide a reliable basis for significant investment.
Fishkin points to data from Semrush, an industry analytics platform, as a case study for his critique. He highlights that Semrush’s analysis of traffic and AI visibility within the “manufacturing & industrial domains” sector does not support the notion that AI visibility correlates with direct traffic. According to Fishkin:
“IF it were the case that AI visibility and direct traffic were correlated, we’d see their trendlines looking similar. But that’s not what’s going on. Measurable traffic from AI assistants (ChatGPT, Claude, Perplexity, Copilot, etc.) fell by -3.9% this year, while direct traffic rose +5.3%.”
Challenging the AI Visibility Narrative
The core of Fishkin’s argument rests on the lack of concrete data and established standards for measuring AI-driven traffic. He notes the difficulty in quantifying the actual volume of users interacting with AI tools for research purposes. Fishkin suggests that many AI Visibility tools and providers are operating on assumptions rather than verifiable data.
As Rand Fishkin elaborates:
“We. Don’t. Know. There’s no gold standard, heck there’s not even a frickin’ tinfoil standard for how much prompt volume there is in a given space.”
He further criticizes the methodologies employed, stating that the best these reports can offer is:
- An indication of minimal traffic from current AI tools.
- An admission of ignorance regarding overall AI-driven traffic volume.
- A visibility ranking based on potentially hypothetical prompt usage.
- Comprehensive data on established channels like search, social, and direct traffic.
Rethinking Investment in AI Metrics
Fishkin cautions against allocating substantial resources and attention to AI Visibility at the expense of other proven marketing channels. He emphasizes that while it’s possible some individuals might use AI tools for research in specific B2B sectors, the lack of comparative data makes it difficult to justify significant strategic shifts.
According to Rand Fishkin:
“I’m not saying no one in aeronautics looks up Boeing’s products in their AI tool. I’m saying that until and unless we know how many people that is, and how it compares to other sources, it’s real weird to throw massive budgets into investing and tracking that one sector at the expense of every other channel.”
Fishkin’s analysis suggests that businesses should exercise caution and demand more robust, verifiable data before making major strategic decisions based on the current state of AI Visibility metrics. He advocates for a continued focus on well-understood and measurable channels, while acknowledging the need for ongoing evaluation as AI technology and its user adoption evolve.
📝 About This Content
This article is based on insights shared by Rand Fishkin on LinkedIn.
📅 Originally posted on September 30, 2026 | View original post on LinkedIn →