Meta’s crawlers hit websites 9.1 billion times in the second quarter of 2026 and sent almost nobody back in return. That single figure, pulled from DataDome’s Q2 2026 AI Traffic Report, captures the widening split between the agents that consume publisher infrastructure and the ones that actually deliver readers.

DataDome’s network processed 17.7 billion AI agent requests between April and June, a 45% jump from Q1’s 12.2 billion. The report draws on 5 trillion signals analyzed daily across more than 400 enterprises. Since January, the network has logged over 30 billion AI agent requests in total, and the monthly curve kept climbing: 4.77 billion in April, 6.29 billion in May, 6.60 billion in June.

Meta drove most of that growth. Its two crawlers do different jobs. Meta-ExternalAgent reads websites to train AI models without sending traffic or compensation back to publishers. Meta-WebIndexer works more like Google’s crawler, indexing pages so Meta AI can answer real-time queries. In Q2, ExternalAgent grew 74% to 5.3 billion requests and WebIndexer grew 163% to 3.75 billion. In June, WebIndexer passed ExternalAgent in monthly volume for the first time, a sign Meta is investing in the answering side of AI as much as the training side.

Crawl volume and referral value are pulling apart. ChatGPT-User, the top agent in Q1, fetched pages 6% less often in Q2. Yet OpenAI’s chatbot still commands 80% to 88% of all AI-driven referral traffic and grew referrals 17% quarter over quarter. Among the rest, Claude referrals more than doubled to 876,000, Perplexity grew 37%, and Grok collapsed 74% to just 24,000 visits.

The distinction matters because publishers have spent the past two years arguing that AI companies use their content without returning referral traffic or other value in exchange. That tension runs through the AI scraping economy, and DataDome’s numbers put figures on it.

The report also flags a new signal worth watching: Model Context Protocol traffic. MCP, the connective layer between AI agents and external tools that Anthropic introduced in late 2024, went from negligible volume to peaks near 500,000 requests a day. Most requests come from AI agents taking inventory through calls such as initialize, tools/list and prompts/list. Rather than reading content, those requests reveal what an agent intends to do before it takes action.

For newsrooms and publishers, the practical message is that bot-or-not detection no longer cuts it. Meta-ExternalAgent, Meta-WebIndexer, ChatGPT-User and a chat session all demand different responses. DataDome recommends agent-level classification, MCP monitoring, and identity validation through standards like Web Bot Auth rather than trusting user-agent strings, which are easily spoofed. Any allowlist granting automatic access based on a trusted agent name is exposed.

Already, 54% of DataDome customers have adopted agent trust policies. The firm frames that as a leading indicator. As Q3 data arrives, the open question is whether Meta’s tilt toward real-time indexing holds, and whether publishers can tell the difference between an agent burning their bandwidth and one bringing them an audience.

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Scott Turow, the bestselling author of “Presumed Innocent,” has filed a copyright infringement lawsuit against Meta. And he’s brought along half of the publishing industry.

Turow and his company S.C.R.I.B.E. joined forces with Hachette, Macmillan, McGraw Hill, Elsevier and Cengage to file a class-action lawsuit in the U.S. District Court for the Southern District of New York. The plaintiffs allege Meta built its Llama language model by copying millions of copyrighted books and journal articles, with direct authorization from CEO Mark Zuckerberg.

The complaint claims Meta “briefly considered licensing deals with major publishers” but reversed course in April 2023 after the question was escalated to Zuckerberg. A Meta employee is quoted in the filing as saying: “If we license one single book, we won’t be able to lean into the fair use strategy.”

The lawsuit cites specific works including Turow’s “Presumed Innocent,” Douglas Preston’s “Impact,” Peter Brown’s “The Wild Robot,” N.K. Jemisin’s “The Fifth Season,” and Lemony Snicket’s “Who Could That Be at This Hour?” The class could include authors with registered copyrights on books with ISBNs or journal articles with DOIs or ISSNs.

“All Americans should understand that the bold future promised by A.I., has been, to paraphrase the investigative writer Alex Reisner, created with stolen words,” Turow said in a statement to NPR. “It is all the more shameful that these violations of the law were undertaken by one of the richest corporations in the world.”

Authors Guild CEO Mary Rasenberger called it “the most flagrant copyright breach in history.” The plaintiffs are seeking statutory damages, a permanent injunction, and an order requiring Meta to destroy all infringing copies.

Meta pushed back sharply. “AI is powering transformative innovations, productivity and creativity for individuals and companies, and courts have rightly found that training AI on copyrighted material can qualify as fair use,” said Nkechi Nneji, a Meta public affairs director. “We will fight this lawsuit aggressively.”

The case enters a complicated legal landscape. A federal judge dismissed a different group of authors’ copyright claims against Meta last June, finding the plaintiffs didn’t present enough evidence of harm. But Anthropic settled with publishers for $1.5 billion last September after a ruling that the company had copied millions of books without consent or compensation.

Whether Turow’s case can distinguish itself from Meta’s previous win — and overcome the “fair use” defense — will be the central question.

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Meta is building a new AI model it plans to sell access to, abandoning the open-source strategy that Mark Zuckerberg championed for years.

The model, codenamed Avocado, is expected to launch next spring as a “closed” system that Meta can monetize directly, according to Bloomberg’s Kurt Wagner and Riley Griffin. This would align Meta with rivals OpenAI and Google, which charge for access to their most capable models.

The shift comes after Llama 4, Meta’s open-source model released earlier this year, disappointed Zuckerberg and Silicon Valley. He sidelined some team members and recruited top AI researchers with multiyear pay packages worth hundreds of millions of dollars.

New Chief AI Officer Alexandr Wang, who joined through Meta’s $14.3 billion acquisition of Scale AI, advocates for closed models. He now leads a group called TBD Lab that reports directly to Zuckerberg.

The team is training Avocado using several third-party models, including Qwen from Chinese tech giant Alibaba. That’s a notable turn for Zuckerberg, who warned on Joe Rogan’s podcast in January that Chinese models could be shaped by state censorship.

Yann LeCun, known as one of AI’s “godfathers” and a major open-source proponent, left Meta recently after years leading its long-term AI research. Some employees had been encouraged to keep him out of the spotlight, Bloomberg reported, because Meta no longer saw him as representative of its AI strategy.

Why it matters for newsrooms: Media organizations evaluating AI tools now face a landscape where even Meta, once the loudest voice for open AI development, is moving toward paid, proprietary systems. That could mean fewer free options for cash-strapped newsrooms and greater dependence on subscription-based AI services from a handful of tech giants.

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