More Information

What Percentage of News Articles Are AI Generated?

Author profile picture

Sam Brown

Sam is an editor, ghostwriter and 7x Top Writer on

• 8 min read

Image of four robots sitting infront of laptops by Mohamed Nohassi on Unsplash

Image by Mohamed Nohassi on Unsplash

Research by Newsguard found that, as of September 2023, 467 news websites out of the 8,000 that they track are entirely AI generated with little to no human oversight. This represents 5.8%.

It’s not only AI content farms though.

As of June 2023, Associated Press (AP) generates 40,000 of its 730,000 articles using AI. This represents 5.5%.

Copy a link to this page

In this article we’ll go beyond just answering what percentage of news articles are AI generated to get a better understanding of the rise of AI-generated news stories, the challenges and controversies of AI-generated content, and look at the future trends and implications of an ever-increasing reliance on AI generated news articles.

Understanding the Rise of AI-Generated News

In recent years, the journalistic landscape has undergone a rapid and profound transformation, driven in large part by the rise of Artificial Intelligence (AI). AI’s presence is increasingly seen in news media, playing a pivotal role in content generation and distribution.

To better understand the significance of this shift, it’s crucial to explore the factors contributing to the rise of AI-generated news.

1. Speed and Efficiency

One of the primary driving forces behind the adoption of AI in news production is its ability to enhance efficiency and speed.

Traditional journalism often involves time-consuming tasks such as data analysis, fact-checking, and even the writing process itself. AI-powered algorithms can handle these tasks swiftly and accurately, freeing up human journalists to focus on more complex aspects of reporting.

This speed and efficiency is particularly valuable in the fast-paced world of breaking news.

2. Reducing Operational Costs

News outlets are under constant pressure to reduce operational costs while maintaining journalistic quality.

AI offers a cost-effective solution by automating various editorial processes. By utilizing AI for tasks like content curation, automated reporting, and data analysis, news outlets can optimize resource allocation and allocate their human talent to areas where their expertise is most needed.

3. Personalization and Engagement

AI-powered recommendation systems have revolutionized the way news is consumed.

These systems analyze user behavior and preferences to deliver personalized news content. This not only keeps readers engaged but also enables news outlets to tailor their content to individual tastes, increasing user retention and advertising revenue.

4. Data Processing

AI’s data processing capabilities have opened doors to data-driven journalism. AI algorithms can sift through vast datasets, identify trends, and generate data-backed news stories.

This approach provides deeper insights into complex issues, making AI a valuable tool for investigative journalism.

5. Reduction of Routine Reporting

Routine reporting, such as financial earnings reports or sports game summaries, can be automated using AI. This allows journalists to concentrate on more in-depth and analytical pieces, emphasizing quality over quantity.

As an example of the impact of the adoption of AI, Goethe Institut reports that “AP (Associated Press) went from producing 300 articles on company earnings reports every quarter to 3,700 through using AI.”

In conclusion, the rise of AI-generated news is not merely a technological development; it’s a response to the evolving demands and challenges of the media industry. The efficiency, cost-effectiveness, personalization, data-driven capabilities, and automation provided by AI are reshaping the way news is produced and consumed.

However, as AI continues to integrate into newsrooms, it also raises ethical and credibility considerations, which we will explore further in this article.

Partial vs. Fully AI-Generated News

In the world of AI-generated news, it’s clear that there’s a spectrum of AI influence in news production.

At one end, there are fully AI-generated news outlets with almost no human oversight, while at the other, there are news organizations that use AI as a supportive tool to enhance human reporting.

Understanding this spectrum is essential to understand the role of AI in journalism.

Fully AI-Generated News

At the extreme end of AI-driven news media are fully AI-generated news outlets. These entities rely almost entirely on artificial intelligence to create news articles from start to finish.

AI algorithms collect data, identify newsworthy events, and generate articles without significant human intervention. These articles are often fact-based (although we’ll explore the reliability of those facts later on in this article) and rapidly produced.

Fully AI-generated news serves specific niches where speed and data-driven reporting are prioritized. For example, financial news updates and sports scores can be efficiently provided by AI systems, allowing for near real-time publishing of information.

Partial AI Assistance

At the other end of the spectrum, many mainstream news organizations have adopted a more cautious approach, often utilizing AI as a complementary tool to support human journalists. This could mean AI assisting in various aspects of news production, such as data analysis, language translation, and content recommendation.

For instance, AI algorithms can assist investigative journalists by sifting through large datasets to uncover hidden patterns or anomalies. In this scenario, AI functions as a research assistant, providing journalists with valuable insights that inform their reporting.

The Hybrid Approach

Some news outlets strike a balance between full AI automation and partial AI assistance. They employ hybrid models, where AI is employed for routine or repetitive tasks, allowing journalists to focus on creative and investigative aspects of reporting. This hybrid approach optimizes resource allocation and editorial output.

The choice between fully AI-generated news and partial AI assistance depends on the news outlet’s objectives, audience, and content requirements. While AI automation offers speed and efficiency, human expertise remains irreplaceable in terms of contextual understanding, analysis, and the ability to navigate ethical and subjective dimensions of journalism.

In the next sections, we will explore the challenges and controversies surrounding AI-generated news, including issues of bias, credibility, and ethical considerations, shedding light on the complex landscape of AI’s role in the media industry.

Challenges and Controversies Surrounding AI-Generated News

Whilst AI has certainly brought efficiency and innovation to news production, it has also ushered in a host of challenges and controversies that demand careful consideration. The integration of AI into journalism has given rise to ethical concerns, credibility issues, and debates over the impact of AI on news quality.

1. Ethical Conundrums

Ethical dilemmas surrounding AI-generated news are among the most pressing concerns.

AI algorithms rely on data, and the quality of that data can be compromised. Biased training data can lead to biased news reporting, perpetuating stereotypes and prejudices. Additionally, the use of AI to create deepfakes or manipulate media content raises concerns about misinformation and its potential to deceive the public.

2. Lack of Editorial Oversight

Fully AI-generated news outlets lack the human editorial oversight that traditional newsrooms provide.

This absence of human judgment can result in factual errors, inappropriate content generation, or the dissemination of false information. This has been widely reported with stories of Gizmodo’s error-strewn articles and false reporting of public figures’ deaths making the (presumably human-penned) headlines.

Ensuring AI-generated content adheres to journalistic standards remains a significant challenge.

3. Trust and Credibility

Maintaining trust and credibility is paramount for news organizations who have often spent decades or even centuries building up the trust of the readers.

When AI is involved in content creation, readers may question the authenticity and objectivity of the news. Trust in journalism relies on the assurance that information is curated and presented by responsible journalists. AI’s role in the process can potentially erode this trust.

4. Job Losses

As in many industries, the automation of reporting tasks through AI can lead to concerns about job losses for journalists.

As newsrooms integrate AI for content generation, some fear that human journalists may be replaced, affecting the diversity and depth of news reporting.

5. Accountability

Determining accountability in the event of errors, misinformation, or ethical breaches in AI-generated news is challenging.

Responsibility is diffused across algorithms, programmers, and news outlets. Clear lines of accountability and mechanisms for addressing errors must be established to maintain journalistic integrity.

The legal and regulatory framework surrounding AI-generated news is evolving.

Questions about copyright, intellectual property rights, and liability in the context of AI content creation require careful consideration. News organizations and policymakers must navigate these legal complexities.

In navigating these challenges and controversies, news outlets must strike a balance between harnessing the benefits of AI-driven efficiency and upholding the ethical and journalistic standards that form the foundation of responsible journalism. The next section will delve into the ways major media outlets are incorporating AI into their news production processes and addressing these concerns.

AI-Generated News in Major Media Outlets

Understandably, some major news outlets are reluctant to reveal the full extent of their AI usage, for fear of eroding the confidence of their readers or revealing proprietary information.

However, we do know that even 4 years ago, one third of all Bloomberg articles are written by their AI writer Cyborg. One can assume that this number has only increased since then.

According to a recent Guardian article, News Corp Australia uses AI to generate more than 3,000 articles per week.

And, as reported at the start of this article, Associated Press (AP) generates 40,000 of its 730,000 yearly articles using AI. Considering the fact that these articles are then syndicated to hundreds of news outlets around the world, this adoption of AI has an outsized impact.

The integration of AI into news production is an ongoing process that is likely to continue shaping the media landscape in profound ways. As we look ahead, several future trends and implications emerge:

1. Hyper-Personalization

AI-driven news recommendation systems are becoming increasingly sophisticated. However, the hyper-personalization of news content may lead to filter bubbles, where readers are exposed only to information that aligns with their existing beliefs, potentially reinforcing polarization.

2. Journalistic Autonomy

While AI can enhance reporting by processing data quickly, there’s a concern about the potential for AI to replace human journalists in routine tasks. This could impact the diversity and depth of news reporting and lead to job displacement.

3. Ethical and Bias Challenges

As AI algorithms determine news content and recommendations, ethical concerns and biases become more prominent. The responsibility to address these issues falls on news organizations and regulators, with questions arising about who holds AI accountable for misinformation or biased reporting.

4. Misinformation vs. Fact-Checking

AI’s role in identifying and combating misinformation is crucial, but the effectiveness of automated fact-checking is an ongoing challenge. The speed of AI may also inadvertently spread false information before corrections can be made.

5. Content Diversity and Creativity

Whilst AI-generated content diversification is a trend, there are concerns about the homogenization of news formats. With AI’s ability to generate content quickly, the risk of formulaic reporting and a lack of editorial creativity becomes apparent.

6. Evolving Regulatory Complexities

The regulatory landscape for AI-generated news is evolving, but complexities arise concerning issues like accountability, transparency, and intellectual property rights. Finding the right balance between innovation and ethical standards remains an ongoing challenge.

7. Shaping the Future of Journalism

As AI’s role in news production expands, the future of journalism is at a crossroads. Striking the right balance between the benefits and pitfalls of AI is a significant challenge. Journalists and society at large must engage in critical discussions to navigate these uncharted waters responsibly.

The journey toward integrating AI into journalism is accompanied by cautious optimism and a need for vigilant oversight. How AI shapes the future of news production will depend on how well we address these concerns, balancing technological advancement with the preservation of journalistic integrity and societal well-being.


Whilst the most accurate available current figure for what percentage of news articles are AI generated is around 5.5%, it is likely that the true number is far higher. Many news outlets have not revealed the extent of their reliance on AI generated content and many figures are outdated or only form part of the puzzle.

For example, as we learned earlier, News Corp Australia uses AI to generate 3,000 articles per week but we do not have an accurate figure for how many articles they publish in total so we can’t make an accurate assessment of what percentage that figure makes up. Additionally, this number only relates to their local news coverage, not national, international, business, sport or any other sector.

It is inevitable that the percentage of news articles that are AI generated will continue to increase over time, as will the discussions around the ethical implications of the widening adoption of AI in the media.

Article originally published 12 September 2023.

Tags: Statistics

If you found this article useful, share it!