A New Era Of AI And Moment for Journalism

As AI absorbs more of journalism’s informational layer, fewer human journalists are deemed necessary. The accelerating adoption of artificia...

As AI absorbs more of journalism’s informational layer, fewer human journalists are deemed necessary.

The accelerating adoption of artificial intelligence marks one of the most consequential turning points in the modern history of journalism. There are, in fact, people still living in a world that no longer exists—persistently attempting to ignore or deny the emergence of a new AI-driven era. 

Organizations should adopt AI with a clear strategy to avoid catastrophic failure and misplaced blame. Without understanding AI’s impact, leaders risk stumbling forward blindly—only to scapegoat others or be blamed when the consequences of unchecked upheavals become impossible to ignore.

Nowhere is this shift more visible than in the recent resignation of the CEO Will Lewis of The Washington Post, which followed newsroom layoffs affecting roughly one-third of its editorial staff. Entire sections—including sports, books, and large portions of international coverage—have been sharply reduced. Most alarmingly, reports indicate that the Post’s Middle East desk has been completely shut down. These cuts represent not merely corporate restructuring, but a structural rupture in how news is produced, distributed, and valued.

While financial pressures and declining advertising revenues are often cited as the primary causes, many within the industry argue that a deeper force is reshaping journalism: artificial intelligence. AI systems are increasingly replacing repetitive tasks that once required large human teams. Journalists who know how to work alongside AI can now augment their productivity, as automated systems handle summarization, basic reporting, headline generation, translation, and content repackaging and those who resist this change or don't unstand AI risk to be part of job cuts. 

Although these tools are frequently framed as productivity aids, their broader economic impact is undeniable. As AI absorbs more of journalism’s informational layer, fewer human journalists are deemed “necessary” to maintain output. In the current moment, it no longer makes economic sense to employ thousands of workers for specialized tasks that can be handled by a single agentic AI at minimal cost.

The Washington Post is not alone. Major international outlets such as Al Jazeera, the BBC, and CNN have all undergone restructuring in recent years, with foreign bureaus downsized or closed and investigative teams consolidated. Many non-technical organizations choose not to explicitly cite AI as a factor behind job cuts. By contrast, technology companies such as AWS, Meta and Google openly acknowledge workforce reductions as part of their transition toward AI-driven automation of core workflows.

At the same time, the audience’s relationship with news is undergoing a profound transformation. Search engines increasingly present AI-generated summaries at the top of results pages, offering users a concise synthesis of “the main facts” without requiring them to click through to the original source. These summaries are generated by models trained, in large part, on the work of journalists themselves. While links remain available, many readers never go further. The result is a slow but steady erosion of traffic to news sites, undermining subscription growth and advertising revenue—the financial backbone of most commercial journalism.

To be clear, the problem is not simply that AI summaries sometimes get facts wrong, though such errors can be dangerous. The more fundamental issue is structural. As AI intermediates the relationship between journalists and audiences, power shifts away from media institutions toward technology platforms and their owners. News organizations risk becoming upstream content suppliers in a business-to-business ecosystem, rather than direct providers of information to the public.

This shift is reinforced by licensing deals between AI companies—such as Google, OpenAI, and others—and major media organizations. These agreements allow AI systems to train on decades of journalistic archives in exchange for much-needed revenue. Given the financial strain facing newsrooms, the temptation is understandable. Yet these deals may obscure a deeper breach: the weakening of the direct bond between journalists and the citizens they serve.

That bond has historically been central to journalism’s public mission. Whether through investigative reporting, foreign correspondence, or local accountability journalism, the profession has existed to inform the public, challenge power, and bear witness. When journalism is primarily consumed as fragmented outputs inside AI-generated mashups, that mission becomes harder to sustain. AI systems respond to queries; they do not curate civic priorities, surface uncomfortable truths unprompted, or act out of a sense of public duty.

The risks are substantial. If journalism is filtered primarily through AI platforms, content that conflicts with the interests or policies of those platforms may be distorted, deprioritized, or quietly suppressed. We are already seeing early signs of this in certain AI-driven search and conversational systems. Moreover, audiences lose one of the great strengths of traditional news consumption: discovering important stories they did not know to ask about, selected by editors exercising human judgment.

There is also a political risk. Media organizations that lack a visible, direct relationship with the public become more vulnerable to attack. If journalism exists largely as anonymous inputs into AI systems, will citizens recognize—or defend—the institutions that produced it when those institutions are pressured by governments or powerful interests?

These changes are unfolding at a time when independent, international journalism is more vital than ever. Global conflict, climate instability, authoritarian resurgence, and technological disruption all demand sustained, credible reporting. Yet the very economic model that supports such work is being hollowed out.

There is no returning to an earlier era, and pretending otherwise is futile. But the trajectory is not inevitable. Media organizations must actively shape how AI is integrated into journalism rather than outsourcing their future to technology companies. This includes investing in high-quality, distinctive reporting; making archives and current work more discoverable on their own terms; and developing in-house AI tools that serve subscribers directly rather than intermediaries.

Public broadcasters, in particular, could play a crucial role by collaborating on AI systems trained on fact-checked, publicly accountable journalism that remains under public control. At the same time, audiences may yet reject impersonal summaries in favor of original, textured reporting—interviews, investigations, and firsthand observation that no model can truly replicate.

Ultimately, the relationship between journalists and their audiences is not a technical detail; it is the foundation of trust, accountability, and democratic function. If that relationship is severed or weakened, journalism loses more than revenue—it loses its purpose.