Summary:

News media companies are employing the emerging field of Artificial Intelligence (AI) via predictive analytics, chat bots, natural language processing, machine learning, and personalisation. Creative use of AI allows for social media virality, target advertising, gender and age identification, sentiment analysis, robo-journalism, speech recognition, automated news briefings, recommendation engines, segmented content, and identifying the legitimacy of content.

Key themes in this report:

• What is Artificial Intelligence, how does it apply to media, and what is its urgency today?
• AI challenges for news media, including ROI, language, and finding talent.
• Natural language processing such as robo-journalism, speech recognition and automated news briefings, sentiment analysis, and recommendation engines.
• Predictive analytics to correlate metrics such as revenue to content usage, gender prediction, age prediction, social media virality, target advertising, and how people become subscribers.
• Machine learning/neural networks to identify whether content is legitimate, the elevation of relevant content, weeding out spam, and more.
• The emerging field of personalisation using AI for information crawling, social media analysis, user profiling, information modeling, and more.
• Whether media companies should build their own AI components or buy — including recommendations for natural language processing, machine learning/neural networks, and predictive analytics.

Who should read the report?

Executives at media companies charged with evaluating AI uses, data analytics strategy, and the use of data to grow audience and revenue and build new efficiencies.

Author:

Martha Stone, CEO of the World Newsmedia Network and founder of the Big Data For Media Conference

Detailed overview:

“Artificial Intelligence (AI): News Media's Next Urgent Investment” provides an executive-level overview of the fast-emerging AI field and its early practical uses by media companies.

The report is broken into three parts:

• Can computers think? In this chapter, AI is defined and early uses and challenges within news media are explored.
• AI categories: Natural language processing, predictive analytics, machine learning, and personalisation are explored — including precise case studies by companies. Detailed cases by the Washington Post and its use of chat bots and Newsday's use of predictive analytics to drive subscriber retention are examined.
• The future: A brief look at Google's DeepMind project explores media integration with AI, along with the question of whether to build or buy with AI — punctuated by precise recommendations of companies in NLP, machine learning, and predictive analytics fields.

Among media companies featured in the new INMA AI report are the Washington Post, Financial Times, Schibsted, Mediacorp, Weather Channel, New York Times, and Newsday.

Breaking down the AI categories, the report delves into precise uses:

• Natural language processing such as robo-journalism, speech recognition and automated news briefings, sentiment analysis, and recommendation engines.
• Predictive analytics to correlate metrics such as revenue to content usage, gender prediction, age prediction, social media virality, target advertising, and how people become subscribers.
• Machine learning/neural networks to identify whether content is legitimate, the elevation of relevant content, weeding out spam, and more.
• The emerging field of personalisation using AI for information crawling, social media analysis, user profiling, information modeling, and more.