Killer or Cure? Navigating AI’s Paradox in Publishing

Google’s rollout of AI Mode in the UK has reignited tensions between online publishers and the search giant. It’s the latest chapter in a long-running battle over fair value exchange, intellectual property, and the economics of the open web.

For publishers, the fear is blunt and immediate: if readers consume answers directly on Google’s page, click-through rates — and the ad and subscription revenue they drive — will collapse.

And there’s data to back this up. Foxglove’s recent research shows that when an AI summary is present, users click through to a link just once in every 100 searches.

This isn’t just a traffic dip. It’s a systemic disruption that could undermine the sustainability of digital publishing as we know it.

Yet here lies the paradox: the same technology threatening to starve publishers of reach also offers the most powerful tools to understand audiences, streamline operations, and build new models of value.

AI may be holding the knife — but it could also be holding the cure.

1. Understand the New Discovery Journey

AI Mode doesn’t just change where people click — it changes how they search. According to Google’s own product leaders, users are now submitting longer, more complex queries. These multi-part questions give AI the chance to synthesise broad, contextual answers in one go.

For publishers, this requires a shift from keyword rankings to search intent mapping — understanding the nuanced questions your audiences ask, the context in which they ask them, and where your brand can deliver value that AI cannot easily summarise.

Case in point: CNET’s 2023 experiment with AI-written articles demonstrated both the opportunity and the risk. Errors led to human rewrites, but the underlying lesson was clear: the discovery journey is already being shaped by AI, whether publishers like it or not.

2. Use Data to Identify and Defend Your Unique Value

AI thrives on the generic. It struggles with content rooted in exclusivity, deep context, and human perspective — the kind of journalism that builds loyalty.

By combining internal engagement data with wider audience trends, publishers can identify which formats are most defensible. That might include investigative journalism, proprietary research, hyper-local coverage, or distinctive visual storytelling.

This insight should drive editorial investment — prioritising content that can’t be reduced to a bullet point or paraphrased into irrelevance.

3. Optimise for AI, Not Just Search

While traditional SEO still matters, AI-first discovery demands new tactics. That includes:

• Structuring content to make your expertise easy to detect and extract.

• Embedding structured data and schema markup to signal credibility.

• Reinforcing authority through consistent cross-channel messaging — from newsletters to podcasts to social.

  
  

Act like a trusted data source, not just a destination.

Le Monde’s partnership with AI-powered news app Artifact is an early example of a traditional publisher working with new discovery dynamics, showing how content strategy and tech partnerships can co-evolve.

4. Harness AI Internally to Improve Agility

The irony is clear: the best way to fight AI’s external threat is to use AI internally.

AI-powered content analytics can help spot trends earlier, analyse performance in near real-time, and forecast audience behaviour with growing accuracy.

These tools also help unify commercial, editorial, and marketing teams — often siloed in traditional newsrooms. With the right leadership, AI can become the connective tissue that turns joined-up thinking into a competitive edge.

Bonnier News in Sweden offers a model for this, using AI to predict article performance pre-publication and automatically generate summaries, subheads, and translations. Their approach shows how AI can support editorial agility without compromising quality.

5. Explore New Value Exchanges

If Google’s AI Mode reduces traffic, publishers must find new ways to monetise attention and assert the value of their content.

That could include:

• Doubling down on owned channels — such as newsletters, podcasts, memberships, and events. Football publishers like The Athletic have excelled at this, converting deep fan engagement into paid subscriptions and live experiences.

• Creating premium, AI-resistant content — like investigative journalism, visual interactives, or nuanced commentary that loses its power when summarised.

• Forming direct partnerships with AI providers. The Associated Press is a pioneer here — striking a deal with OpenAI in 2023 to license parts of its news archive dating back to 1985. In return, AP gained access to OpenAI’s tech and insight. This is a clear recognition of news content’s value in AI development — and a blueprint for others.

• Experimenting with new data products. Reuters, for instance, now provides AI-ready structured newsfeeds tailored for business clients, investment platforms, and even AI model training.

  
  

Whatever the model, the goal is the same: a fair value exchange for content — grounded in a deep, data-driven understanding of your audience and where they place value.

The Real Choice: Reinvention or Retreat

AI is rewriting the rules of discovery, consumption, and competition. For publishers, it presents an existential challenge — and a once-in-a-generation opportunity.

AI can kill the old business model. But it also offers the tools to build a better one.

The choice is simple: treat it as a passive threat — or embrace it as an active strategic partner.

The Associated Press didn’t wait to be disintermediated — it got paid. Bonnier News didn’t fear automation — it made it work for its editors. CNET’s stumble showed the risks, but also the reality: AI is already in the newsroom.

The future of publishing won’t be written by AI — but it will be shaped by those who know how to use it.