What Should a Head of Growth Report to the Board About AI Search?

Report five lines. None of them is a ranking table.

Baseline mention rate by engine. Share of voice against named competitors. AI-attributed sessions and revenue, broken out by engine and by page. Cost per AI-attributed opportunity, sitting next to the same number for paid. A before-and-after on the specific buyer questions where you shipped content.

That is the whole slide. Rankings move to the appendix, where they belong, because rank is now an input to citation, not a proxy for pipeline.

What the old slide looked like

For a decade the growth report had a comfortable shape. Keywords won, positions gained, organic sessions climbing, a conversion rate applied at the end. Everyone in the room understood it, which was part of the problem. "We moved from position seven to position three on our top commercial term" sounded like progress even in quarters where nothing closed.

It worked because the mechanism was stable. A buyer typed a query, saw ten links, clicked one. Position predicted clicks, clicks predicted sessions, sessions predicted pipeline. Break any link in that chain and the slide stops being evidence and starts being decoration.

The chain broke. 71 percent of B2B buyers use AI chatbots (G2, 2026), which means a large share of your market asks an assistant for a shortlist before it ever sees a results page. The assistant answers in prose and names three or four companies. There is no position three in that answer. There is named, or not named.

What actually changed

Two things, and a board deserves to hear them separately.

Being found and being cited became different jobs. An engine assembles an answer from the sources it trusts for that specific question, and that set does not map cleanly onto the top ten blue links. Each engine draws differently, too. Gemini grounds its answers in Google Search, so your classic rankings still carry real weight there. ChatGPT, Claude, and Perplexity reach elsewhere. One number cannot describe four behaviors, which is why a single composite "visibility score" is the worst thing you can put in front of a board. It is not auditable, and the first question any decent director asks is what moved and why. We will not ship a number like that, and neither should you.

Then the economics inverted. AI referrals are a small slice of total traffic for most B2B sites, usually low single digits. Lead with session volume and you lose the room. Lead with value per visit instead: LLM-referred traffic converts at 4.4x the baseline (Semrush, 2025), and AI search referrals grew 527 percent year over year (Search Engine Land, 2025). Small channel, high intent, steep curve. That is a very different argument than "traffic is up."

The five lines, and what to say about each

Baseline mention rate, per engine. The percentage of your tracked buyer questions where an assistant names you at all, measured separately on ChatGPT, Claude, Gemini, and Perplexity. Most early-growth B2B SaaS companies start near zero on competitive category terms, and that is fine. A zero you measured beats a number you guessed.

Share of voice against named competitors. Not "we appeared sometimes." The actual companies the engines recommend instead of you, ranked by how often they get named. This is the line that turns the conversation from marketing to strategy, because it tells your CEO what a buyer hears about the category before anyone reaches your site.

AI-attributed sessions and revenue, by engine and by page. A dollar figure with a name on both ends. Revenue from ChatGPT, from this specific post, this week. This is not theoretical: Bosten Shoes went from unmentioned to the number-one recommended leather shoe brand in El Salvador and booked its first ChatGPT-attributed sale in under 30 days. One engine, one page, one sale, traced end to end. If you track leads but not closed sales yet, show projected pipeline from a per-lead value and label it a projection on the slide. Mixing the two is how growth leaders lose credibility in a single meeting. Here is what that 30-day loop looks like for a funded B2B SaaS.

Cost per AI-attributed opportunity, beside paid. Boards do not fund channels, they fund comparisons. Use the same attribution window and the same conversion definition your paid report uses, or the comparison is theater.

Before-and-after on specific questions. You published against five questions where you were invisible last quarter. Show the mention rate on those exact questions now, with the wording reused verbatim. Change the phrasing and you have changed the test.

What to say about the numbers you cannot prove

Say it out loud, on the slide. Many AI engines strip or obscure the referrer, so a real ChatGPT visit can land in analytics looking like direct traffic. The honest framing is that your AI-attributed number is a floor, not a ceiling, and that you corroborate it two ways: self-reported attribution on demo forms, and branded search lift measured against flat non-branded organic. We have written about why so much AI traffic hides as direct, and how closed-loop attribution differs from dark-traffic estimation.

Naming the uncertainty is not weakness. It is the thing that makes the rest of the numbers believable.

Build version one this week

The reporting line changed from "we are visible" to "visibility produced this." Everyone shows you rank. Your job in that room is to show revenue, and to be specific about which engine, which page, and how much.

You do not need a quarter to start. Run the ten questions your buyers actually ask through all four engines, write down who gets named and who does not, and run the identical questions again in thirty days. Our free AI visibility check gives you that starting number without a sales call; Clark runs the same loop daily and ties the conversions back when they land.