AI in media begins its move from efficiency to new information ecosystem

By Dorinne Hoss

Head of Marketing

Arc XP

Chicago, Illinois, USA

Connect

Artificial Intelligence (AI) is transforming how media companies operate, from automating routine tasks to enabling entirely new forms of storytelling.

At our recent Arc XP Connect event in London, we hosted a discussion with four AI experts to learn where AI is headed next for media organisations. They outlined two distinct phases in AI's trajectory:

1. The current phase, focused on efficiency and optimisation.
2. The next phase, a forthcoming revolution in the information ecosystem.

Below are key takeaways from the discussion, giving media professionals a look at what's next in AI.

Phase one: efficiency and optimisation in newsrooms

Media companies are currently in phase one of AI adoption: using AI to streamline and optimise existing workflows.

David Caswell, an AI consultant with experience at the BBC, the Tribune Company, and Yahoo, explained how many media organisations are deploying AI to enhance familiar tasks, from content tagging to audience targeting. "It's a perfectly reasonable place to start," Caswell said. "It makes sense to automate the stuff you already know in order to optimise the status quo and make your life more efficient as it is."

Mark Watkins, principal solutions architect at AWS, shared a practical example: AI-powered article tagging. In the past, tagging thousands of articles manually could take months. Now, AI systems can tag content in days, significantly reducing costs and freeing up human resources for more strategic tasks.

A standout example of efficiency through AI came from Venkat Varalu, vice president of data and analytics at The Washington Post. He described its "smart metering" system, which uses a deep-learning algorithm to optimise paywalls.

The AI system adapts dynamically, learning from real-time data to provide the best experience for each user. This approach allows The Post to compete in the crowded digital space, especially against big players, like Google, by using AI to level the playing field.

For journalists, this efficiency phase is more than just a cost-saver; it's a new tool for quality journalism. Lars Adrian Giske, an investigative journalist at Mediahuset iTromsø in Norway, illustrated how AI has sped up his investigative processes, cutting research time by as much as 80% by sifting through archives for newsworthy documents.

Giske emphasised AI enables journalists to focus on stories that might otherwise remain hidden, democratising investigative journalism by making it accessible to smaller newsrooms with limited resources.

Phase two: a new information ecosystem

While phase one is largely about making current processes more efficient, phase two represents a more profound shift: AI as a force reshaping the information ecosystem itself.

"There is a second phase where the functionality that AI is offering, not just to the news industry but right across the information ecosystem, adds up to something that is very, very different than the existing ecosystem," Caswell said. "We'll go through a fairly radical transformation that may be as large as the transformation that social created. In my view, it will likely be larger."

One of the most exciting developments in phase two will be AI-driven storytelling.

"I think we'll see totally new experiences," Giske said. "For example, letting people explore stories in a different way than today, asking questions that maybe aren't apparent in the story. We can use the data from an investigative project and have that available to the reader for them to explore within the context of that story space."

The panelists also predicted hyper-personalised storytelling, where AI tailors the tone, format, and even length of articles based on the reader's style and available time.

"Currently when we talk about personalisation, we are talking about moving modules around personalising a recommendation or what the next article is. But I think personalisation will go significantly deeper to changing the tone of the article depending on my style of reading, changing the length of the article, depending on how much time I have," Varalu said.

"That will include formats as well. If I prefer to read an article that has a video, there will automatically be videos created. These are all things we are talking about already."

AI will also enable a new breed of journalism that spans vast information landscapes. For example, Caswell discussed the concept of "reasoning models," like OpenAI's latest tool that can apply significant computational power during the task execution itself, rather than just during training.

These advanced tools allow for simple investigative journalism at scale, offering more detailed, precise outputs that can be trusted by both readers and journalists.

The future: innovation and responsibility in the AI-driven media landscape

The possibilities phase two opens up are endless, but so are the responsibilities. With AI's growing influence, the panelists agreed media companies must use it wisely, focusing on where it can make the most impact without forcing it where it's unnecessary.

Varalu cautioned against overusing AI, suggesting that organisations concentrate on high-value tasks where AI can truly shine - like automation of repetitive tasks or optimising digital content - rather than applying AI across the board.

As Giske emphasised, AI should support journalism's democratic mission, helping to hold power accountable and inform the public. For media companies embracing AI's future phases thoughtfully and creatively, this technology holds the potential not only to increase efficiency but to create an entirely new, dynamic, and personalised way for people to experience news.

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About Dorinne Hoss

Dorinne Hoss is head of marketing at Arc XP in Chicago, Illinois, USA. Dorinne can be reached at [email protected] or @dorinnehoss.

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