Will AI Dominate in Broadcasting in 2019?

In almost every area of modern technology, we’re beginning to see the implementation of AI/ML (artificial intelligence and machine learning). AI/ML made inroads in broadcasting and video production in 2018, but these industries are still a ways out from utilizing this technology to its fullest potential. Whether or not it fully takes off this year, or even the next, is a matter of debate in industry trend reports.

In the last year, the adoption of AI/ML in media and broadcasting jumped from 2% to 13% just between April and September. At the 2018 Masters Tournament, IBM’s AI tech was used to identify and compile highlights based on expressions, gestures, commentary, and on-screen graphics. Video producers could then compile highlight reels and broadcast them in near-real-time to viewers. In this and many other scenarios, AI/ML has the potential to significantly speed up production and workflow. 

There are, however, several reasons that broadcasting may lag behind other industries in adopting and deploying AI/ML. The most immediate concern for many broadcasters is that they can’t effectively monetise it. The cost of implementing it may outweigh its potential advantages. 

AI/ML is also best suited to sifting through large amounts of data. To large broadcasters who have plenty of viewer data to work with, this is AI/ML’s biggest benefit. Contrastly, FTA (free-to-air) broadcasters who are moving into OTT often don’t have enough viewer data for AI/ML to be accurate or useful. These companies need to build out their databases beforehand, which requires a data management team, and will inevitably slow their adoption of new technology. 

Finally, the broadcast industry tends to be cautious. AI/ML will undoubtedly see more interest and adoption this year, but broadcasters will need to see significant ROI before an industry-defining change is made. More likely, AI/ML will see moderate experimentation, while transitioning to IP workflows continues to be the priority in 2019.