Your Buyer's AI Already Researched You. You Weren't There.
Anthropic just plugged Claude into FactSet, LSEG, and DocuSign. Enterprise deals are being researched before your sales team knows the prospect exists. Most founders have no idea this is happening.
The deal already happened. You just weren't in it.
That's the uncomfortable implication of what Anthropic announced on February 24. Claude's new Cowork plugin suite connects directly to FactSet, LSEG, DocuSign, MSCI, and S&P Global. These aren't communication tools. These are the exact systems that analysts, procurement officers, and CFOs use to do vendor due diligence before any sales conversation begins.
Think about what that means.
A portfolio company's head of finance opens Claude, asks it to research the top three options in your category, and Claude queries FactSet. It pulls public financial signals, coverage density, market positioning. It checks LSEG for analyst mentions and deal history. It cross-references DocuSign contract volume as a proxy for customer momentum. It builds a vendor shortlist. Your sales team gets an inbound request three weeks later — if they get one at all.
What did Claude say about you?
Here's the thing about enterprise procurement: it never looked the way you thought it did. The demo you got excited about? The prospect already knew the answer before they booked it. They were validating, not discovering. The real discovery phase — the part where your category gets defined, your competitors get ranked, and you get included or excluded — that happens before your CRM even knows the prospect exists.
AI has simply made this invisible layer visible, and then automated it.
Bain & Company's 2026 enterprise AI research describes what's happening: AI platforms are becoming "enterprise operating systems" with agent orchestration embedded into core business workflows. They're not auxiliary tools. They are the workflow. And the data these agents reference when they build their analysis is the same data that determines who shows up in the shortlist.
This is not a search problem. It's a presence problem.
Most founders, when they hear "AI visibility," think about Google AI Overviews or ChatGPT search. They think about getting cited in consumer-facing answers. That's real — LLM referrals now convert at 2-5x the rate of organic search — but it's not the whole picture.
Enterprise deal flow doesn't happen through ChatGPT searches. It happens through structured queries inside financial data platforms. It happens through analysts asking Claude to summarize the competitive landscape using the same FactSet terminals they've used for a decade. It happens through procurement teams who now have an AI assistant that can cross-reference LSEG market data, DocuSign deal signals, and press coverage in one prompt.
And here's the gap: almost no one is building authority inside those layers.
You can have a perfect SEO footprint. You can rank for every relevant keyword. You can have a beautiful content strategy. None of that matters when Claude is querying FactSet for signals about your company's market presence and finds a thin, inconsistent, or absent data profile.
I built AuthorityTech on one principle: earned media is infrastructure. Before I understood why, I knew the outcome — clients who had real press coverage in authoritative outlets consistently outperformed clients who didn't. The algorithm reasons didn't matter yet. The data spoke first.
What's becoming clear now is that earned media isn't just SEO infrastructure. It's not just AI search infrastructure. It's the citation layer that every AI agent — whether it's a consumer-facing ChatGPT or an enterprise Claude querying FactSet — uses to determine who is credible, who is relevant, and who should be in the answer.
Research on AI citation sources shows that the brands dominating AI answers are those with deep earned authority footprints in the sources AI engines weight as authoritative. Not the brands with the most content. The brands with the most credible third-party signal.
That's Machine Relations. Not as a marketing tactic. As the infrastructure for how you get included in any AI-mediated decision — consumer or enterprise.
The window is specific. Anthropic's own analysts note that enterprise adoption of Claude plugins typically takes 9-10 months from announcement to widespread deployment. That clock started February 24. The companies who are building their authority footprint in the sources Claude now queries — while their competitors are still arguing about whether AI search is real — will be the ones already in the shortlist when deployment reaches scale.
This is the same moment as Google in 2003. Except the stakes are higher and the window is shorter.
The buyers in your category are 9-10 months from running AI-assisted due diligence as a default behavior. The question isn't whether you'll be in the room. The question is whether you're building the presence right now that puts you there.
One statistic to hold onto: Profound's research shows up to 90% of cited sources in AI answers can change week to week. The citation layer is not locked. It's being fought over right now, in real time. The companies earning authoritative press coverage — not just publishing content, but earning placement in the publications AI engines trust — are the companies filling those citation slots.
Here's what I know:
Enterprise deals are being won and lost before the first sales email. The procurement research has moved inside AI agents that query data platforms most founders have never thought about. And the factor that determines whether you're in those answers isn't your SEO score or your content volume. It's whether you've built the kind of press and authority footprint that AI agents recognize as credible signal.
That's what we fix. That's the visibility audit — not as a vanity exercise, but as a map of where you exist in the data layer your buyers' AI agents are about to start reading.
The deal is already being researched. Are you in it?