Over 2,200 U.S. Local Newspapers Closed Since 2005 as AI Automation Emerges in Newsrooms

The ongoing crisis in local journalism was underscored recently when Jacob Eiting, identified as "iap/acc," announced via social media the impending closure of his hometown's local newspaper. Eiting's tweet, posted on September 9, 2025, reflected a sentiment of both dismay and innovative thinking, stating, > "The local paper in my hometown is shutting down and I have half a mind to write an LLM monstrosity that could just automate the whole thing." This comment highlights the severe challenges facing community news outlets and sparks discussion on artificial intelligence's potential, albeit controversial, role in their future.

The closure of Eiting's local paper is part of a broader, alarming trend across the United States. Between 2005 and 2021, approximately 2,200 American local print newspapers ceased operations, leading to a significant increase in "news deserts" where communities lack adequate local coverage. This decline has resulted in a more than 50% reduction in the number of American newspaper journalists from 2008 to 2020. The loss of these vital institutions has been linked to decreased civic engagement, increased government waste, and heightened political polarization at the local level.

The primary drivers behind this widespread contraction include plummeting advertising revenues, a secular shift of readers and advertisers to digital platforms, and high production costs. Traditional newspapers have struggled to adapt their business models to the internet era, where consumers often expect news for free. Digital advertising revenue, while growing, has not been sufficient to offset the substantial losses from print circulation and advertising sales. This financial strain often leads to layoffs, reduced print frequency, or complete shutdowns.

Amid this challenging landscape, artificial intelligence, particularly large language models (LLMs), is being explored as a potential tool for news production. AI can automate "low-effort" reporting tasks such as generating articles on sports scores, financial reports, or police blotters, freeing human journalists for more in-depth investigative work. Proponents suggest AI could improve efficiency, expand coverage to niche topics, and potentially help news organizations operate more sustainably by reducing content creation costs. Some newsrooms are already experimenting with AI for tasks like transcribing interviews, suggesting headlines, and sorting news pitches.

However, the integration of AI into journalism is not without significant concerns. Critics warn of the risk of job displacement for human journalists and the potential for AI systems to introduce errors or "hallucinations" that could damage journalistic credibility. There are also ethical questions regarding the lack of human oversight, potential biases in AI-generated content, and the risk of accelerating misinformation. Maintaining trust with the audience is paramount, and the industry is grappling with how to ensure accuracy and transparency when using AI for news generation.

The contemplation of an "LLM monstrosity" to automate a struggling local paper, as tweeted by Jacob Eiting, encapsulates the complex future of local journalism. While AI offers avenues for efficiency and expanded content, its role must be carefully managed to preserve journalistic integrity and the unique human element of reporting. The ongoing debate centers on whether AI will serve as a vital support system to struggling newsrooms or further erode the human-led journalism essential for informed communities. The industry continues to seek viable models that balance technological innovation with the fundamental principles of accurate and trustworthy news delivery.