The Rise of AI Journalism

07.02.2020 · By Farah Khalique

The biggest names in news and publishing across the world are harnessing the power of Artificial Intelligence (AI) and Machine Learning (ML) to transform storytelling. CNN, The Washington Post, Reuters, Sky and The Guardian are among the wave of publishing maestros using AI to modernise how writers find and tell stories, as well as fine-tune content for subscribers.

LOYAL AI is spearheading this revolution by developing cutting-edge journalism tools to eliminate pain points for writers and newsrooms. Our expert team is incorporating Machine Learning technologies into an exciting new suite of editorial workflow tools – to spark creativity and make work effortless for the world’s content creators. 

Read on to find out how newsrooms are adopting AI and how LOYAL AI’s productivity tools for journalists can help you get the best out of your content. 

AI for time-intensive tasks

“No, the robots are not going to take over journalism. Yes, the machines might soon be able to do much routine journalism labour. But the reality and the potential of AI, machine learning, and data processing is to give journalists new powers of discovery, creation and connection.” 

Professor Charlie Beckett at the London School of Economics (LSE) wrote these words in the opening page of a comprehensive report into how AI technologies are revolutionising the media industry. The university’s media think tank, Polis, published the report in collaboration with the Google News Initiative, back in November. 

71 news organisations from 32 countries already use AI for time-intensive tasks. For instance, newsgathering, production and distribution. It paints a picture of how this technology is already transforming their working lives. Most feedback came from Europe and the US, but also as far afield as India and Botswana. 

You can read the full Polis report here

Journalism AI meeting
Journalism AI meeting, in Google France headquarter, Paris. On 17th of May, 2019.

Why are media organisations using AI?

It’s a tricky time for publishers. Newsrooms are under pressure to deliver high-quality, fresh content in real-time with less money on the table. Indeed, the report described a “general aspiration to use any efficiencies to free up resources for enhanced newsroom functionality and for new or improved content and services.” 

68% Make journalists’ work more efficient 

45% Deliver more relevant content to users 

18% Improve business efficiency

Source: Polis report

The Polis report’s definition of AI is a collection of ideas, technologies, and techniques that relate to a computer system’s capacity to perform tasks normally that require human intelligence. But AI is in its infancy. So, in reality we are talking about “machine learning” or “natural language processing”. Programmes that are created and trained by humans can carry out simple automation or process data to reveal new insights. We’re a while away from Space Odyssey’s Hal Computer. 

How do they use AI?

Just under half use AI for newsgathering

Newsgathering: sourcing of information, content discovery and story idea generation. Along with identifying trends, investigations, event or issue monitoring, and extracting information or content. Journalists use AI tools to sift through reams of information like public announcements and social media posts, and filter it based on predefined categories.

Image recognition APIs [Application Programme Interfaces] for analytics and journalism – genders and ages in images, genders in text. 

Neural Networks for photo tagging and Natural Language sentiment (Google Cloud APIs).

The next step is to use this filtered raw material to tell a story. For example, Machine learning algorithms can help journalists spot trends and story ideas that might otherwise have passed them by. The report cited a publication in Mexico that used a machine learning algorithm to calculate the difference between the number of homicides reported in Mexican news versus the government’s official numbers.


Two-thirds use AI journalism tools for production

Production: content creation, editing, and packaging for different formats and platforms. Also, text, image and video creation, and repurposing content for different audiences. AI can help with mundane, yet mandatory, tasks. For example, translating, transcribing, spell checking and fact checking.  

“Our sub-editors and journalists currently use Grammarly, which employs artificial intelligence techniques, to help check grammar and spelling for our English articles” Source: Contributing publisher, Polis report

“We built an automated tagger for our newspaper’s articles (which tags articles with topics/keywords – formerly done by editors), built into our CMS [Content Management System].” Source: Contributing publisher, Polis report

Finnish public service broadcaster Yle even built its own robot journalist, Voitto. It produces hundreds of pieces of content a week, filled with words and pictures. Voitto combines rules-based methods and machine learning experimentations. It then produces content for Yle’s news app, newsletters and Twitter accounts. Remember all the celebrities filmed at the Sussexes Royal Wedding in 2018? Sky News used facial recognition technology to spot them arriving at the ceremony.

Just over half use AI for distribution

Distribution: personalisation, marketing, and finding audiences. Also, understanding user behaviour and monetisation/subscriptions. This is where it gets interesting. Publishers can get the most out of their existing subscribers and find new ones. 

The Times, for example, spent three months using machine learning to relate 10 user metrics to 16 different pieces of content metadata such as headlines and article format to understand what worked best for readers. 

The results led to changes in the amount and type of content created for certain sections or platforms and a sharpened focus on boosting engagement. For example, which stories to promote via social media. It made their content creation strategy more efficient and, in terms of reader attention and subscription renewal, more effective. 

Get ahead with LOYAL AI 

It’s clear that the smartest publishers are already using AI journalism tools to take newsrooms into the next era of journalism. The beauty is that even smaller publishers and individuals can maximise their gains by using these “smart” tools to get the most bang for their buck.

LOYAL AI is at the forefront of this sea change. Our developers are building affordable, “off the shelf” AI journalism tools for writers from all backgrounds. Whether you are a freelancer, blogger, influencer, editor or managing a team of hundreds of journalists, our tools are designed to help you minimise admin and maximise output.

Join the AI revolution. Discover LOYAL AI’s Editorial Insights Assistant to research your content faster and the Social Media Embed Assistant to find the best social media posts to embed into your content. Both will be available via Google Chrome extensions


Discover how these publishers are already using artificial intelligence to find breaking news and report it in record time.

1 The Washington Post’s Heliograf: A robo-reporting tool was used to report on the 2016 summer Olympics and congressional races on Election Day. 

2 The Press Association’s RADAR: An automated news service set up by the Press Association and Urbs Media. It helps “to write local news stories at a frequency and precision impossible otherwise” – 50,000 in the first three months. Speedy!

3 Texty’s Leprosy of the Land: A piece of investigative journalism made possible by a “machine learning model” to find traces of illegal amber mining in Ukraine. 

4 The New York Times’s Project Feels: “A project to understand and predict the emotional impact of Times articles”, and then serve personalised ads accordingly. 

5 Bloomberg’s Cyborg: An automated system that uses AI and extraction. This is used to identify key data points in companies’ earnings reports and publish headlines and articles in seconds.