Exa Labs, the AI search startup building a search engine specifically for AI agents, has closed a $250 million funding round at a $2.2 billion valuation, according to Bloomberg, more than tripling its valuation since last fall and signaling that investors see significant room for new players as the search market undergoes its most significant shift since ChatGPT arrived.

The round was led by Andreessen Horowitz, which is making a pointed bet on the next era of search. Sarah Wang, a general partner at the firm who worked on the deal, noted that Andreessen’s own history traces back to Netscape, and that the firm sees AI agents as the next tectonic shift in how people interact with the web.

“Literally, the DNA is at our firm,” Wang said. “As we think about AI—this is the mother of all waves. We also think we are entering a new era for search.”

Exa CEO William Bryk said the company is betting that agents will search the web more than humans for the first time this year, a milestone he describes as an important turning point. “There are billions of humans doing searches—there are going to be trillions of agents, like, very soon,” Bryk said in an interview. “So we just want to accelerate on all fronts.”

The company, which has about 100 employees and offices in San Francisco, Zurich, and Singapore, has grown its customer query volume from roughly 100 million per month in April of last year to about 1 billion per month in April of this year. Customers include Cursor, Cognition, and HubSpot. Exa has also partnered with Google to give Gemini access to its search engine.

Exa is part of a broader wave of AI search startups—including Tavily, TinyFish, and Parallel Web Systems (led by former Twitter CEO Parag Agrawal, which recently raised $100 million at a $2 billion valuation from Sequoia)—that are all vying to serve the coming world where AI agents search on users’ behalf rather than humans clicking through links.

The other side of the valuation

The $2.2 billion figure is an extraordinary vote of confidence in Exa’s vision. But as our coverage of the AI scraping economy has detailed, Exa’s business model is inseparable from that valuation story. Exa (formerly known as Metaphor) is in the business of selling publisher content to AI companies. Its search engine is built to serve AI agents. The customers paying for that access are building products that use publisher content as raw material.

The economics have been a point of contention. Researcher Matthew Scott Goldstein, who has been tracking the data broker layer between publishers and AI companies, identified 21 vendors operating in this space in a recent report, Exa among them. “Publishers create it. Exa crawls it. AI companies buy it. Publishers get nothing,” he wrote in a LinkedIn post.

Exa has not disclosed its revenue. It has not announced any licensing agreements with publishers. And the company is now valued, by one of the most prominent venture firms in the world, at $2.2 billion—built on infrastructure that runs through content publishers produce.

The question of whether and how AI search companies will compensate publishers for the content that powers them has not been answered. The Andreessen Horowitz investment suggests investors believe the AI search market is real and large. What it does not resolve is who bears the cost of producing the content that makes these search engines worth building.

The post A startup that sells publisher content to AI companies is now worth $2.2 billion appeared first on The Media Copilot.

OpenAI is strengthening its approach to identifying AI-generated content, announcing a multi-layered provenance system that combines cryptographic metadata, invisible watermarking, and a public verification tool, though the company acknowledges no single method is foolproof.

The centerpiece of the update is a new partnership with Google DeepMind to embed SynthID watermarking into images generated through ChatGPT, Codex, and the OpenAI API. SynthID, Google’s invisible watermarking technology, is designed to survive transformations like screenshots and file format changes that can strip standard metadata from content.

The two approaches are meant to work together. C2PA — the open technical standard backed by the Coalition for Content Provenance and Authenticity, a cross-industry group — uses metadata and cryptographic signatures to carry information about where content came from, who created it, and how it was edited. But that metadata can be lost. SynthID provides a backup signal that persists through more transformations.

“C2PA helps content carry detailed context; SynthID helps preserve a signal when metadata does not survive,” OpenAI said in a blog post. “Together, they make provenance more resilient than either layer would be on its own.”

OpenAI also became a C2PA Conforming Generator Product — meaning platforms can now reliably read, preserve, and pass along the provenance information attached to OpenAI-generated content. The company has been adding Content Credentials to images since 2024, when it began with DALL·E 3, later extending to ImageGen and Sora.

A public verification tool

OpenAI is also previewing a public verification tool at openai.com/verify that lets people check whether an uploaded image was generated on ChatGPT, the OpenAI API, or Codex. The tool checks for both Content Credentials and SynthID watermarks.

The approach is deliberately cautious. If no metadata or watermark is detected, the tool will not conclude the image was not generated with OpenAI tools — since provenance signals can be stripped.

“If no metadata or watermark is detected, for example, the tool will not make a definitive conclusion about whether the image was generated with OpenAI tools since provenance signals can in some cases be stripped,” the company said.

At launch, the verification tool is limited to content generated by OpenAI. The company said it aims to support cross-industry verification across platforms in the coming months.

The limits of provenance

The announcement arrives as the question of AI content authentication has become acutely relevant. A Florida Tribune investigation published this week identified a network of AI-generated fake local news sites — complete with fabricated reporters and AI-recycled content — built specifically to manipulate search results. Provenance tools like SynthID and C2PA would not have prevented that scheme, which used content scraped from real outlets and processed through AI. But they could make it harder for the operators of such sites to pass their output as genuinely human-produced.

“No single provenance technique is enough on its own,” OpenAI acknowledged. The company’s answer is the layered approach — shared standards, durable watermarking, and public verification — in the hope of building “a more interoperable provenance ecosystem” over time.

The broader industry has been moving in similar directions. Adobe has embedded Content Credentials in its Firefly-generated images, and Google has been rolling out SynthID across its own products. But adoption remains voluntary, and the tools do nothing to address content that was AI-generated before provenance standards existed — or content deliberately created outside these systems.

The post OpenAI builds a new system to identify AI-generated images appeared first on The Media Copilot.

By The Copilot & Musso Media Editor

The media industry has spent years optimizing for clicks, traffic, and scale. But in B2B, the stakes are different.

A single decision can involve millions of dollars and require input from 5 to 15 stakeholders. That changes everything about how content is created, distributed, and measured.

At the same time, AI is reshaping how audiences discover information. Fewer clicks. More summaries. More intermediaries. Which means fewer chances to capture attention, but higher stakes when you do.

That’s the shift happening in media that’s beneath the surface of headlines about lawsuits and AI slop. In this episode of The Media Copilot podcast, host Pete Pachal talks with Keith Turco, CEO of Madison Logic, to unpack the shift to better understand how AI is changing not just media, but B2B publishers.

The result is a fundamental shift:  Quality over quantity. Precision over reach. Outcomes over impressions.

For publishers, marketers, and media operators, this is not just a trend. It is a structural change in how value is created.

What we cover

• Why B2B media is moving from impressions to performance-driven outcomes
• The rise of buying groups and how they reshape content strategy
• What “geek chic” means and why measurement is now the differentiator
• How AI acts as a “refiner,” not a replacement, in marketing workflows
• The shift from one-to-many messaging to one-to-one and one-to-few targeting
• Why podcasts and audio are becoming critical in the B2B media mix
• How the “at-work state of mind” blurs personal and professional media consumption
• What publishers are still getting wrong about ROI and measurement
• Why niche, high-intent audiences are more valuable than ever
• The growing role of multi-channel strategies across CTV, social, and audio

Listen or watch:

• YouTube
• Spotify
• Apple Podcasts

Key takeaways

• B2B decisions are group decisions. Messaging must reach multiple stakeholders with different priorities.
• AI enhances targeting and measurement. It refines strategy rather than replacing human insight.
• Performance is everything. Marketers now demand clear ROI, not just visibility.
• Attention is fragmented but more valuable. Fewer interactions, but higher intent.
• Content must be hyper-relevant. One-to-one and one-to-few messaging outperform broad reach.
• Audio is underrated. Podcasts capture decision-makers in high-value moments.
• Publishers must evolve. The future belongs to those who can prove outcomes, not just deliver audiences.

About the 👤

Keith Turco 

Learn more about Madison Logic:

🌐 https://www.madisonlogic.com/

🔗 https://www.linkedin.com/company/madison-logic/

🐦 https://twitter.com/MadisonLogic 

About the show: To explore more conversations like this and see what’s new, visit the freshly updated Media Copilot website at mediacopilot.ai. You’ll find new episodes, expanded resources, and tools designed for journalists, communicators, and media leaders navigating the fast-changing world of AI. It’s the home base for everything Media Copilot and it’s just getting started.

Enjoyed this episode?

Subscribe to The Media Copilot on Substack, Apple Podcasts, Spotify, or your favorite app. On YouTube?  Tap the Like button and Subscribe to the YouTube channel.

For more AI tools and resources built for media professionals, visit MediaCopilot.ai.

Produced by Pete Pachal and Executive Producer Michele Musso
Edited by the Musso Media Team 

Music: “Favorite” by Alexander Nakarada, licensed under CC BY 4.0

All rights reserved. © AnyWho Media 2026

The post How AI is changing B2B media appeared first on The Media Copilot.

New research from Profound argues LinkedIn has become the most-cited domain for professional queries across major AI search platforms — a notable shift for publishers, brands, and creators chasing visibility.

LinkedIn has quietly become one of the most important source layers in AI search for professional topics, according to new research from Profound — and that should get the attention of publishers, B2B marketers, and anyone trying to understand where large language models are pulling authority signals from.

Profound says LinkedIn is now the No. 1 cited domain for professional queries across six major AI platforms: ChatGPT, Gemini, Google AI Overviews, Google AI Mode, Microsoft Copilot, and Perplexity. The firm also says LinkedIn’s overall domain rank in ChatGPT citations moved from about No. 11 in November 2025 to about No. 5 by mid-February 2026.

The more interesting detail is not just the rank jump. It is where the citations are coming from. Profound says feed posts and long-form LinkedIn articles together rose from 26.9% to 34.9% of LinkedIn citation types during the three-month period it studied, while profile citations fell sharply. In other words, AI systems may be leaning less on static identity pages and more on published content that looks like ongoing expertise.

If that pattern holds, it has implications well beyond LinkedIn itself. For media companies, it suggests AI answer engines are increasingly willing to surface platform-native content when it looks current, attributable, and topically relevant. For independent journalists, analysts, and newsletter writers, it suggests that posting on LinkedIn is not just social promotion anymore. It may also be search distribution.

That does not make LinkedIn a substitute for publishing on your own domain. Quite the opposite. Platform-owned distribution can change fast, and Profound’s analysis is based on proprietary datasets and methodology that deserve some caution. The report combines real-user prompt and citation data from ChatGPT with a synthetic prompt basket run across multiple AI systems. That is useful directional evidence, but it is not the same thing as an independently replicated industry benchmark.

Still, the directional signal is hard to ignore. AI answer engines have long been hungry for content that is concise, timely, clearly authored, and tied to real-world expertise. LinkedIn happens to package all of that neatly: identity, topic clustering, publication recency, and engagement signals in one place. That gives it an advantage when models need a plausible source for professional queries.

For publishers, the threat is familiar. Yet another slice of authority may be shifting to a platform that sits between creators and audiences. But there is also a practical lesson here. If newsroom leaders, consultants, and media brands want their analysis to surface in AI-generated answers, they may need to think less about LinkedIn as a marketing afterthought and more as part of their distribution stack.

The trap would be overreading one vendor’s research into a universal rule. Profound is making an argument, not establishing a law of physics. Even so, the company’s data lines up with a larger industry reality: AI search is increasingly reward­ing content that looks native to the question being asked. For professional topics, that may now mean LinkedIn has a bigger seat at the table than many publishers would like.

The post LinkedIn is now the top-cited domain in professional AI search, Profound says appeared first on The Media Copilot.