AI breaks the hamster wheel of journalism

The hamster wheel has been a defining metaphor for what it’s like to work in contemporary journalism: an experience marked by relentless motion but often too little progress to show for it.

In 2026, the wheel may finally start to fall apart — and, if so, generative AI will be responsible.

The hamster wheel metaphor first gained traction as a diagnosis of what had gone wrong with journalism in the digital era. Dean Starkman, writing in 2010, crystallized the problem: “The Hamster Wheel isn’t speed; it’s motion for motion’s sake. The Hamster Wheel is volume without thought. It is news panic, a lack of discipline, an inability to say no.”

Each wave of technological change has added rotational fuel to the wheel’s velocity.

The early web required that many newspaper journalists learn content management systems and repurpose their work for online spaces while maintaining their print duties.

Social media platforms layered on demands to engage audiences where they gathered, to participate in every conversation as fast as possible, and make the news literally dance to new trends.

Mobile technology untethered journalism from the desktop, creating an expectation of always-on availability and real-time responsiveness. The 24-hour news cycle, already exhausting in the cable television era, became even more frenetic in a decade dominated by push notifications and pull-to-refresh feeds.

Yet through all these transformations — web, social, mobile — a fundamental assumption remained: The hamster wheel was dependent on humans running it. New technologies might change the pace of work and new tools might make certain tasks easier, but there was no question about the engine behind it all: the human journalist as an irreplaceable driver of content creation.

The wheel spun faster and faster, but it was still a person — however exhausted — running it.

Generative AI complicates that assumption. It doesn’t automatically remove humans from media work, but it reshapes what journalism work is — and with it, how journalists understand their value and purpose. With tools like ChatGPT, Gemini, and Claude, certain aspects of journalism production can now be automated or augmented in unprecedented ways. Articles can be drafted, headlines tested, social posts crafted — all with varying degrees of human involvement.

But here’s the crucial distinction: AI’s capability to write doesn’t eliminate the need for journalism; it forces a reckoning with what constitutes journalism’s most central skills. If AI can competently handle routine writing tasks, this doesn’t mean journalists become obsolete. It means journalists must clarify what makes their work distinctly valuable.

The question isn’t whether humans are needed, but which human capacities matter most.

Previous technologies asked journalists to do more of what they already did — faster, across more platforms, in more formats. AI asks something different: Which parts of journalism are best supported by humans and which parts can be better supported by machines?

When journalists are given dedicated time to work with AI technologies — removed from their regular production duties — researchers observe something remarkable. “They see it as a break, a moment that they can reflect and engage in things — not just on the hamster wheel, if you like, of production,” notes Bronwyn Jones, research lead at the Responsible Innovation Centre for Public Media Futures, an independent research center hosted by the BBC.

Whether the introduction of AI creates breathing room or simply raises expectations depends in part on how newsrooms respond, including through the priorities of managers. If journalists’ bosses care solely about “optimization,” “efficiency,” and “cost-cutting,” that doesn’t bode well for AI’s impact on journalism work. If they care about making their journalism as valuable as possible, that’s a different story.

This is the central fork in the road for journalism’s AI era from a managerial perspective: Down one path is the substitution approach (AI as a tool to do the same work faster and with fewer people, hamster wheel-style), and down the other is a complementarity logic (AI as a tool to do work that was previously unfathomable, reaching underserved audiences in new ways and altogether unlocking greater value in news).

The breaking of the hamster wheel’s fundamental premise — that humans must run it — creates space for reimagining what journalism could be if not organized around acceleration as its governing logic. The hamster wheel might finally come apart because journalists learn to say no to the rat race of digital demands — and say yes to a long-overdue reckoning about what journalism is for.