The Next Wave of Disruption: Emerging Market Media Use of Artificial Intelligence and Machine Learning

"In frontier and emerging media markets across the globe, there are many new opportunities in newsrooms to innovate through artificial intelligence, machine learning and data processing."

This report looks into how the media in countries in Latin America (LatAm) and Central and Eastern Europe (CEE) are using artificial intelligence and machine learning (AI/ML) in their newsrooms. The goal of the research discussed in the report was to better understand how the news sector in emerging news media markets uses AI/ML to collect, analyse, and share data to grow their audiences and/or revenues and to explore some of the barriers to AI usage. The ultimate objective is to find new ways to drive successful digital transformation in business and journalism by understanding how newsrooms in these markets can use technology to develop a data- and user-led approach to newsgathering, content creation, distribution, or generating revenues. The research was carried out in the first quarter of 2021 by International Media Support (IMS), together with the Latin American Centre for Investigative Journalism (The CLIP) and The Fix.

Researchers collected data from 44 media publishers from 20 countries in the two regions to explore the practical ways media in these markets are using, and can use, AI. A range of smaller and bigger newsrooms (including print, TV and radio), as well as academics and local experts, were consulted. Media managers hailed from tech-savvy independent, innovative, and entrepreneurial media that were more than five years old. They included digital editors, data specialists, editor-in-chiefs, directors, and chief technical officers.

The report explores the AI/ML solutions used in each region, including information on newsroom budget and resource allocations, as well as the resource needs of media organisations in each region in relation to AI/ML. In summary, the research found that in LatAm only a handful of media organisations are embracing AI or machine learning in house, most notably in Argentina, Perú, and México, and none is embracing technology as a long-term solution. Most of the news organisations consulted are implementing AI through vendors or third-party solutions, and there is strong appetite for more. The research also shows that the media sector lacks basic knowledge of the capabilities needed to create AI-savvy newsrooms.

In CEE, digital natives (helped by strong academic traditions, particularly in engineering and mathematics) are embracing AI/ML solutions, and the region has produced a few AI/ML-based third-party solution providers with global reach or ambitions. Competition for talent is a major bottleneck, as media have to compete with the global outsourcing of information technology (IT) jobs to the region. The other challenge is state pressure on media, especially in such markets as Russia or Belarus, which makes long-term planning and investment impractical. The research also shows that the comparative advantage in the technology sector in CEE is being hampered by a relatively low level of cooperation between media, business, and academia.

How AI is being used in each region is also examined in detail in the report. Examples include: the use of AI for subscription services; personalisation and automation to engage readers and drive them to become subscribers; and the use of AI for headline testing and to obtain user feedback. The most common AI/ML use in LatAm was for predictive patterns to generate new content and understand visitor patterns, while in CEE it was used for the automated generation of texts. The data showed little use of AI for intelligent invoice management, customer or post-sale services, or automatic content generation for social media.

The findings point towards the power of collaborative approaches between media, research institutions, and third-party solution providers, as many applications or ventures are beyond the scope of a single outlet due to the resources needed, availability of data, or other barriers to entry.

The report concludes with a list of recommendations, which include:

• Establishing new public-private partnerships/collaborations with AI research hubs that adopt a problem-solving approach to identify where AI/ML and data processing strategies (not tools) can provide a catalytic push towards business development for media;
• Conducting more research to identify and map how AI solutions can match the needs of small, media, and large media in emerging markets;
• Providing support and interventions that have as their main purpose to identify what processes and challenges AI can address; and
• Supporting long-term training and education programmes with media and research institutes from emerging markets to share best practices and test use cases, with a focus on reaching and engaging new local audiences through data and editorial analytics and automated content.

The report also offers "10 Tips for media to get into AI" to help media organisations develop better strategies for using AI to improve the news production process.