AI enables broadcasters to make more informed decisions, improve their efficiency, and open the potential to create inventive new experiences for their audiences. It also has the potential to save costs, enabling more media outlets to distribute content just like the major networks.

Using AI analytics, broadcasters can deliver on its wider promise to advertisers to deliver unprecedented granularity of insight into their audience, faster and more effectively than ever before. AI’s usefulness in automating metadata has also been well documented, and more exciting applications of this mass-data-crunching ability are beginning to emerge.

For example, the 2022 World Cup in Qatar 12 dedicated tracking cameras mounted underneath the roof of the stadium, tracking the ball and up to 29 data points of each individual player, 50 times per second so that their exact relative positions on the pitch could be calculated in real-time. The ball also contained inertial sensors, the data from which could be combined, mapped onto a 3D model, and then used to assess offside calls and the other elements of the game.

Indeed, AI makes it easy for broadcasters to get data from many different sources and evaluate it in real-time. They can use AI to gain insights into levels of viewer engagement and make more informed decisions about what content should be aired and when it should be aired. This has the potential to result in increased ratings as well as increased revenue for the content owner.

AI is also assisting in the automation of routine tasks that would otherwise require human interaction. Like searching, locating and retrieving a specific image from a massive MAM system. Leveraging automated processes allows media companies to increase their overall productivity, save time, and cut costs. In yet another example, voice recognition technology driven by AI can automatically translate audio recordings into text, which may then be used for additional analysis.

While some may worry that AI systems are replacing human crew, in fact, the technology is currently being employed to cover events that would otherwise not be broadcast.

The British Broadcasting Corporation (BBC) recently carried out research on the matter (“AI in Production”). The internal study made use of inexpensive 4K UHD static PTZ cameras to simulate a two or three camera set-up.

The 4K resolution recorded by these cameras is much higher than is needed for broadcast. This means that different parts (HD cropping) of the footage can be created for the different media platforms that broadcasters must support.

Using these low-cost static cameras allows smaller live events to be covered with a one-man crew. It also allows an outside broadcast team to cover a greater number of locations. Including those that don’t need a larger setup.

The uses for AI and machine learning in broadcast are constantly expanding to enhance the user experience. AI technology is even being used to speed up the process of recoloring black and white footage. It uses archive material and color information from similar frames. This makes it possible to reduce the time to colorize five seconds of film from 30 minutes down to 30 seconds.

In a similar vein of streamlined workflows, automatically identifying presenters or guests on camera can be automated with the help of facial recognition technology. This technology is now in wide use at TV stations that use robotic camera systems in the studio. Facial—and object—tracking keeps the talent perfectly centered or otherwise in frame at all times, with no human intervention needed

Computer vision algorithms can also be used to recognize items in videos or photographs and deliver extra information about them in real-time. This could include providing detailed descriptions of people or objects seen on camera during a live broadcast.

Several broadcast equipment suppliers are now offering AI-enhanced systems to give sports commentators real-time data so that they can tell a better story of the game for the audience. These software tools enable the real-time collection and organization of artificial intelligence data from dozens of leagues. This result is increased audience engagement and participation for broadcasters, who can now share stories that have not been told before.

At the end of the day, using AI allows the industry to create and imagine things not possible before. The technology brings the creative and technical ability to distil topic, image, EPG correction and context from video content—all automatically and in real-time. With this, users can explore the full potential behind every video segment and create new content value for their clients.

Far from a threat, AI has become an essential tool for achieving success in today’s digital age. It is highly likely that as the technology continues to advance over time, more novel applications of AI will be developed and help shape the way media companies operate both today and in the future.