Profound Just Hit $1B. The Data It Generates Will Make Most CMOs Uncomfortable.

On Tuesday, Profound raised $96 million at a $1 billion valuation. Lightspeed led the round. Sequoia, Kleiner Perkins, and South Park Commons followed. Fortune ran an exclusive. The headline framed it as a story about AI threatening search.

It isn't. It's a story about what happens when 700 enterprise companies — including 10% of the Fortune 500 — are finally forced to look at a number they've been avoiding.

That number is their AI citation frequency. How often does ChatGPT mention your brand when users ask questions in your category? How often does Perplexity recommend you over a competitor? What does Gemini say about you when someone types "best [your product] 2026"? Profound shows you this in real-time. And the answer, for most established brands, is going to land like a punch.

Here's what Profound's own internal research reveals: up to 90% of cited sources in AI answers can change from week to week. Different AI models draw from largely distinct source sets. The brand that dominated Google rankings for a decade is not automatically the brand that AI engines cite. That's a new competitive landscape, and most companies are just now buying the instruments that let them see it.

But the instrument telling you that you're invisible doesn't make you visible. And this is the part of the Profound story that matters more than the valuation.

The measurement layer for AI visibility has now reached unicorn scale. Seven hundred companies are paying to find out where they stand. What they're finding is a citation gap between who they think they are in their category and who the machines think they are. That gap is not a tracking problem. It is a content authority problem. And it is primarily closed by one thing: earned media in publications that AI engines weight as authoritative. Search Engine Land's 2026 GEO guide documents the same reality: the brands dominating AI answers are those with the deepest earned authority footprints, not just the best-optimized owned content.

This is why Lightspeed partner Sachin Patel's framing is the most important sentence in the Fortune piece: "There's this massive migration happening, where consumer attention is moving from search engines into answer engines. Profound is building the system of record for marketers in that world."

The system of record for marketers in that world. Think about what that means. In the Google era, the system of record was your Google Analytics account — it told you who found you, how, and from where. Profound is the same play for the AI era. But there's a fundamental difference in what the data reveals. Google Analytics showed you traffic sources. Profound shows you citation authority — or the lack of it.

And citation authority is not built through bidding or on-page optimization. AuthorityTech's analysis across 200+ client programs shows that 82–89% of AI-generated answers cite third-party earned media over brand-owned content. It is built through earning the right coverage in the right places over time.

The brands that will look at their Profound dashboard and feel confident are not the brands that ran the best GEO campaigns. They're the brands that spent the last 18 months building systematic earned media footprints in authoritative publications. Forbes features. TechCrunch coverage. WSJ mentions. The placements that made it into AI training data. The placements that persist in RAG retrieval because the publishing domains carry the trust signals AI systems are built to follow.

Everyone else is going to open Profound and see a problem they've been ignoring.

The concept at the center of all of this — the framework that explains both why earned media dominates AI citations and what to do about it — is Machine Relations: the discipline Jaxon Parrott coined in 2024 that treats AI engine citations as a strategic asset, not a side effect of search optimization.

Traditional PR convinced humans to cover you. Machine Relations convinces the machines — because the machines inherit the trust that humans established through authoritative coverage. When Forbes writes that your company is worth knowing about, that signal doesn't just live in the Forbes archive. It gets ingested into AI training runs, retrieved by RAG systems, and used as the basis for AI-generated recommendations for years.

Conductor's 2026 research shows 97% of digital leaders report positive ROI from GEO efforts, and 32% named it their top strategic priority this year. But what that research also reveals is the ceiling: brand-owned GEO has limits that earned authority does not. The brands accounting for the other 82–89% of AI citations aren't outranking you on technical GEO. They're the brands that earned the third-party coverage that AI systems weight as trusted source material.

The uncomfortable truth the Profound dashboard is about to surface across 700 enterprise marketing teams: your content team has been optimizing the thing that accounts for 11–18% of AI citations. Your competitors who figured out the earned media play first own the other 82–89%.

That's not a GEO problem. That's a fundamental misallocation of where the citation authority actually comes from. And now there's a unicorn-valued measurement platform making that misallocation visible to every CMO with a subscription.

The question is whether they use the data to fix the right thing. If you want to understand what fixing the right thing actually looks like — the earned media model that closes the gap Profound is showing you — run a visibility audit and see where the gaps are for your brand specifically.

The dashboard is here. What you do with it is the question.

Frequently Asked Questions

What is Profound, and why does its $1B valuation matter?

Profound is an AI visibility tracking platform that shows brands how frequently AI engines like ChatGPT, Gemini, and Perplexity mention and recommend them. Its $1 billion valuation signals that AI citation authority has become a mainstream enterprise marketing concern — 700 companies, including 10% of the Fortune 500, now actively pay to track it. The valuation matters because it confirms that the AI visibility problem is real, measurable, and at institutional scale. The harder question is what brands do with the data.

Why do most brands find their AI citation scores are lower than expected?

Profound's internal research shows up to 90% of cited sources in AI answers can change over time, and different AI models draw from distinct source sets. Most brands have optimized their owned content for Google search — structured Schema, keywords, backlinks — but haven't built the third-party earned media footprint that AI engines weight most heavily. According to AuthorityTech's citation analysis, 82–89% of AI-generated answers cite third-party earned media over brand-owned content. Lower-than-expected scores reflect this imbalance: good GEO foundation, thin earned authority layer.

What actually moves an AI citation score after you see the data?

The measurement layer (Profound, SiteSignal, others) shows you the gap. The earned media layer closes it. Brands that improve AI citation frequency fastest are those that combine citation-optimized owned content with consistent Tier 1 earned media placements — Forbes profiles, TechCrunch coverage, industry publication features. The trust signal a third-party placement carries is categorically different from brand-owned content, and AI training pipelines are built to amplify it. Machine Relations is the discipline that integrates both layers into a systematic program.