When we talk about innovation and particularly the use of AI, large European companies tend to dominate the conversation. Theirs are often groundbreaking use cases, implemented in structures that allow them to move quickly because they have long embraced digital transformation.

Today’s blog is going to be different. We are going to surface use cases from Latin America.

Rede Gazeta

At Rede Gazeta in Brazil, AI is being used to make it easier for users to find information, and its applications go beyond the newsroom.  

“We are doing small experiments that could be relevant for our company and, mainly, to improve the experience of our users,” said Ronaldo Henrique da Cruz, subscriptions manager.

He described a new project his team is working on: 

“In March of this year, the income tax declaration period begins. Many users have questions about tax declaration, and we have a lot of content in our collection that can help users clarify these doubts.  

“This project has always worked with the support of our call centre, which assisted users and sent questions to specialists, then our agents received the response from the specialist and responded to users — a very long journey. 

“In 2023, we started using a chatbot that searched for articles that we inserted into a platform we use called Zendesk, and the number of users who were able to resolve their doubts with the articles was very high, greatly reducing contact with our agents (but, even so, we had to provide human support for some users). 

“For 2024, we will use AI to find these articles in our collection with more precision, making the search even easier and expanding the recommendation of more articles that may make sense to those doing the searches.” 

Ovaciones

Similarly, Pedro Iván Quintana Garcia has found that it is valuable to assess where GenAI can be truly useful in saving time for staff and where to be more skeptical. He is a director at Ovaciones, a small newspaper in Mexico City that is part of a larger organisation, Organización Editorial Mexicana. 

“When I was offered this job six months ago, I saw it as an opportunity to explore how we could use AI to do better things in a medium that operates with the bare essential staff,” he said. 

“What have we done? Firstly, within OEM, we created a working group with editors from other parts of the country. We started by working on discovering what can be done, what we could use it for, whether there had been any independent local experiences, and what they learned from them.

“One of the first steps with this group was to demonstrate that SEO-optimised headlines generated by ChatGPT are as effective as those created by an editor who knows they will be evaluated. We ran headline tests comparing those created by AI with those generated by expert editors in Chartbeat and found no significant differences in traffic favouring one over the other. 

“Also, it became clear to us that the autogenerative AI is not yet ready to produce reliable texts. The tendency of the model we tested to hallucinate is hard to eradicate. However, we found that by restricting generation only to the data provided, it is an efficient ally and helps us optimise our content to make it more effective for digital media readership. 

“At this point, we want to share the knowledge we have acquired with more newsrooms to try to standardise the prompts and presets so that we obtain similar results across the organisation. Also, we want to train the organisation’s specialised reporters in the analysis of official documents, such as audit reports. 

“Lastly, we have used AI to generate generic images, enhance audio recordings, and improve the quality of photographs. Additionally, we have reached an institutional agreement on how we will use Artificial Intelligence within OEM.”

If you’d like to subscribe to my bi-weekly newsletter, INMA members can do so here.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .