The AI hangover: What smart publishers will do in 2026

Forget the AI gold rush. Sustainable journalism rests on 3 truths: original insight, authentic audience engagement, and owned data infrastructure.

The past two years have been marked by a kind of collective mania. News organizations, from legacy giants to scrappy independents, have chased every AI announcement with the fervor of prospectors following rumors of gold.

Chatbots for everything. AI-generated summaries nobody asked for. Experimental tools that consumed developer hours and produced nothing but conference fodder.

In 2026, the hangover arrives. 

Not because AI failed, it hasn’t. But because the newsrooms that survive and thrive will be the ones that finally ask the right question: What problem are we actually solving?

Looking at Nic Newman’s 2026 media trends report, it really is still an open question for the industry. 

Publishers are still figuring out how to actually use generative AI in their newsrooms, from newsgathering to distribution. In the meantime, they’re pursuing other strategies to stay competitive.

That means investing heavily in distinctive, human-centered content and expanding beyond articles into video and other formats.

They’re also working to make their content more flexible so it can be easily repackaged and personalized across different platforms.

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The reckoning

I’ve spent the last year talking to publishers across four continents, from weeklies to digital-firsts. What I’ve heard repeatedly is a growing disillusionment with AI projects that looked impressive in pitch decks but delivered nothing for the bottom line or the journalism.

One European publisher told me they’d spent six months building an AI tool to auto-generate social media posts. It worked. The posts were adequate.

But their social traffic didn’t increase, their subscriptions didn’t grow, and their social editor, the one who actually understood their audience, felt increasingly that they wasted their time. They quietly shelved the project.

This story, with minor variations, is playing out everywhere.

What really matters

The newsrooms that will win the next decade aren’t the ones with the most sophisticated AI. They’re the ones that remember three fundamental truths:

1) Journalism creates value through original insight

No AI can cultivate a source. No language model can sit through a city council meeting for eighteen months, noticing the pattern that leads to an investigation. No algorithm can feel in its gut that something’s wrong with the official story.

The newsrooms that invest in reporters, in shoe leather, in expertise, in time, will produce work that no synthetic system can replicate. There are, and there are going to be AI tools that help with certain aspects of this. The question is about their ROI.

2) Authentic audience engagement beats algorithmic optimization

We’ve spent years trying to game platforms, A/B testing headlines into oblivion, chasing clicks that never converted to loyalty.

The publishers seeing real subscriber growth are the ones building genuine relationships, through newsletters that feel like letters from a friend, through events that create community, through membership models that make readers feel like stakeholders.

But building those relationships at scale requires knowing who your readers are, what they value, and how they engage. That requires the infrastructure to capture and act on that knowledge.

Part of this work is deeply human. It cannot be automated, and it shouldn’t be.

3) Infrastructure determines what’s possible

Here’s where the AI hype has actually obscured something important: the newsrooms that will be positioned to use AI effectively are the ones that first built solid data foundations.

You can’t personalize content if you don’t understand your readers. You can’t automate workflows if your systems don’t talk to each other. You can’t measure what matters if you’re drowning in vanity metrics.

The newsrooms that will use AI effectively are the ones that first built the infrastructure to understand their readers.

The infrastructure imperative

This is the unsexy work that doesn’t make headlines at journalism conferences.

It’s CRM systems that actually track reader behavior. It’s analytics that connect content performance to conversion. It’s email infrastructure that enables genuine personalization, not just first-name mail merge, but understanding what each subscriber actually wants to read.

It’s connecting content performance to subscriber behavior, so you know not just what gets clicks but what builds loyalty.

The smartest independent publishers I know have stopped asking “What can AI do?” and started asking “What do we need to know about our readers, and how do we get that knowledge into the hands of people who can act on it?”

This shift isn’t anti-technology. It’s pro-outcome, and ultimately pro-AI.

It means investing in platforms that put publishers in control of their data rather than extracting it.

It means building the foundation for a sophisticated audience strategy now, so you’re ready when AI becomes genuinely useful.

Slovak publisher Dennik N understood this a decade ago, which is why they built their own tools rather than renting capabilities from platforms that could change terms at any moment.

Austrian weekly Falter, Croatian Telegram.hr, and investigative outlets across Central Europe have followed similar paths, prioritizing ownership of their reader relationships and the systems that support them.

These organizations aren’t Luddites. They’re pragmatists who understand that sustainable journalism requires technology infrastructure that generates genuine reader understanding.

The projects that will survive

This doesn’t mean AI disappears from newsrooms. But the projects that survive 2026’s reckoning will share common traits: they’ll support journalism rather than replace it, they’ll solve specific problems rather than chase trends, and they’ll build on foundations of owned data and understood audiences.

I’ve seen AI work beautifully when it helps reporters search archives faster, when it surfaces patterns in data that humans can then investigate, and when it handles the mechanical work of transcription so journalists can focus on analysis.

These applications succeed because they were built on solid data foundations and they amplify human capability rather than substituting for it.

The projects that will die are the ones built to impress funders or wow conference audiences: the chatbots nobody uses, the auto-generated content that erodes trust, the “AI-powered” features that are really just novelty seeking dressed in technological language.

A different kind of question

In 2026, the question won’t be “How do we use AI?”

It will be “How do we build journalism that matters, supported by technology we control, for audiences we genuinely understand.”

The organizations that answer this question well will share a few characteristics.

They’ll own their subscriber data and reader relationships. They’ll have infrastructure that connects the dots between content, engagement, and revenue.

They’ll invest in people, journalists who uncover stories, and audience specialists who build community. And yes, they’ll use AI where it helps, but as a tool, not a strategy.

The hype cycle is ending. What comes next requires harder work and clearer thinking.

But it’s also more honest about what journalism actually is: human beings finding and telling stories that matter, building trust with readers one relationship at a time.

That’s not something that can be automated. And that’s exactly the point.