Last Year Proved AI Isn’t The End Of Publishing, So What Can We Learn About AI Adoption From The Industry?
For the past two years, one question has loomed over media, marketing and content businesses alike: will AI kill publishing? At a recent Association of Online Publishers (AOP) industry event, it became clear that the question is increasingly outdated. The more relevant one now is: how fast can organisations learn from the publishers who are already using AI and navigating AI adoption to grow, not shrink?
Across newsrooms, ad operations and data teams, the story emerging is consistent. When applied with clear guardrails and editorial judgement, AI doesn’t replace creativity. It removes friction. It gives time back. And it’s already reshaping what scale, localisation and audience engagement look like in practice.
So what can we learn from the UK’s publishing leaders as AI becomes an ever-more present part of our lives?
Helping Us Do What We Do Best
Newsquest’s experience with its generative Copy Creator tool is perhaps the most powerful example of AI as an enabler rather than a threat. It started with a modest goal: automate the routine stories that consumed local reporters’ days, such as press releases, road closures, planning notices and community updates.
These aren’t glamorous tasks, but they’re essential, especially for local papers reporting on the things that make a difference to their readers day-to-day. The problem was that they trapped journalists behind desks, stopping them going out and investigating the really interesting stories we all want to read.
With Copy Creator, reporters now work from notes on one side of the screen and AI-generated draft copy on the other. They edit, refine and apply their editorial standards, while the model learns from their decisions over time. Crucially, only trained, specialist AI-assisted reporters use the tool—people grounded in data protection, bias awareness and editorial judgement.
The result?
- 12,000 AI-assisted stories a month
- 11% growth in page views
- 35% increase in subscriptions year-on-year
More importantly, reporters are back out in their communities doing original, on-the-ground storytelling. Entire regions that were once economically unviable now have meaningful local coverage again.
The lesson? AI works at its best when it absorbs routine workload so humans can focus on the things only they can do—originality, creativity and truly valuable strategy.
AI As A Discovery Engine
At The New York Times, automated metadata enrichment was used to digitise and structure millions of archived articles. This creates the backbone of TimesMachine, a browsable 150-year archive that is now offered as a subscriber perk. The technology has turned what was once a huge set of dormant assets into a living product that people can easily engage with and enjoy.
With the incoming wave of agentic AI systems, AI’s ability to turn vast swathes of unused data into useable insights or tools will be pushed to another level. For lean teams under constant output pressure, this kind of orchestration shifts AI from a novelty into core infrastructure, helping humans to understand trends quickly and easily, and apply those learnings to whatever task they are doing.
Ultimately, this use case has the potential to train teams with past content and drive better-informed decision-making across various industries.
Scaling Regional Growth With Translation
While it is Estonia’s leading publisher, Delfi Meedia also has significant audience reach outside of the country, including Lithuania and Latvia. With this cross-border reach comes complexity, from the practicalities of publishing news in multiple languages to the need to factor in regional nuances that make all the difference to readers.
The business has seen a multitude of wins using AI, on top of straightforward automation: translation, transcription and tagging. Over time, Delfi has been able to combine general translation tools like DeepL with models fine-tuned for Baltic languages. It has unlocked scalable content sharing between Estonia, Latvia and Lithuania without sacrificing local nuance.
This matters far beyond news. Any organisation facing language, regulatory or cultural fragmentation can now realistically imagine regional scaling without multiplying headcount at the same pace.
AI doesn’t just globalise content. When used carefully, it preserves its local character while extending its reach.
AI Is Changing Economics, Not Ethics
While there is a lot of enthusiasm around the value-add of AI in the publishing industry, this is partnered with a serious focus on governance. From copyright disputes to bias in training data, the risks are real, and businesses must keep these in mind as they explore what AI tools can do for them.
Common themes emerged:
- Clear purpose limitation for data use
- Strong chain of title and rights verification
- Transparent labelling of AI-assisted content
- Ongoing bias testing and human oversight
In other words, the organisations winning with AI adoption aren’t the ones moving fastest—they’re the ones building the strongest foundations.
The most striking theme from the AOP event wasn’t technical sophistication, but confidence and operational certainty.
Across journalism, localisation, ad tech, analytics and audience strategy, the same pattern is emerging:
- AI handles the repetitive, while humans focus on the meaningful
- Scale increases without compromising quality
- New markets open without incremental cost increases
This is why the familiar framing around whether AI replaces creators is starting to feel misplaced. The evidence suggests the opposite. Used well, AI is becoming the infrastructure layer that allows creators, editors, analysts and communities to operate at a higher level.
If 2024 was about experimentation, and 2025 about governance, then 2026 may be the year organisations stop fearing AI and start putting into practice what publishers already have:
AI isn’t the end of publishing. It may well be its next growth engine. And the lessons extend far beyond the newsroom.
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