94% of B2B buyers use AI search: how do you measure the ROI?

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If you’re still treating AI search as a future problem, the buyers in your funnel disagree. Forrester found that 94% of business buyers now use AI search during the purchasing process, ranking it above vendor websites, product experts, and sales reps. B2C isn’t lagging far behind: NielsenIQ puts AI-assisted product research at 42% of consumers.

That’s not a trend to monitor. That’s a channel that’s already eating your attribution model.

The measurement problem

The challenge with AI search ROI is structural. When a buyer asks ChatGPT, Perplexity, or Google’s AI Overviews about your product category and your brand shows up in the response, there’s no click, no UTM parameter, and no session in your analytics. The customer shows up later in your funnel already partially convinced, with no visible referral source to credit.

Standard last-touch and even multi-touch attribution models were not designed for this. You cannot measure what you cannot track, and AI search surfaces answers without the hyperlinks that traditional measurement depends on.

Why this matters for operators

For solopreneurs and small teams running lean attribution setups, this creates a real budget justification problem. If AI search is influencing a meaningful share of inbound leads but showing up as direct traffic or dark social, you’re potentially underinvesting in the content and brand signals that AI models pull from.

The Ahrefs piece by Louise Linehan addresses how to work around the attribution gap and build a practical measurement framework for AI search visibility. Given that the article comes from the team that built Ahrefs’ Brand Radar (a tool explicitly designed to track brand visibility in AI chatbots versus the open web), the framing is practitioner-level rather than theoretical.

If your content strategy doesn’t account for how AI models represent your brand, the 94% stat is a reason to fix that now rather than after your pipeline numbers get confusing.

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