AI in Broadcast: Accelerated Adoption

Summary

The surge in AI (artificial intelligence) adoption in broadcasting services is rapidly enhancing program quality. AI offers significant cost efficiency and benefits, particularly as its cost drops significantly. 

AI is now well-recognized in both science and the broadcast industry, driving its adoption. The decreasing cost of AI makes it more accessible and practical for broadcasters. 

While many technologies share similarities, AI and Machine Learning (ML) stand out for their direct utility, especially in commercial enterprises like broadcasting. Mark Mayne of IBC notes, "Although AI is often overhyped, practical use cases are now emerging in broadcast services."

Emergence of AI in Broadcast

Broadcasters are now using machine learning algorithms to enhance the viewer experience. For instance, computer vision algorithms can recognize objects in videos or photos and provide real-time information about them, including detailed descriptions of people or objects seen on camera during live broadcasts. 

AI’s emergence as an effective tool for engaging viewers is evident in Sky News' 2018 broadcast of Harry and Meghan’s royal wedding, where facial recognition technology identified and displayed information about royals and celebrities. This example shows how AI has moved beyond improving workflows to creating new broadcast experiences. 

AI and ML technologies are increasingly used in broadcasting, enabling broadcasters to make informed decisions, improve efficiency, and create new, unforgettable audience experiences. An IBC webinar (2022-23) explored AI’s utility in detail, discussing how AI analytics can provide unprecedented insights to the audience faster and more effectively than before.

AI and Machine Learning in Broadcast – The Difference

Machine learning and AI are often used interchangeably but have distinct roles. AI mimics the human brain, using algorithms for logic and advanced math to process information. Machine learning, a subset of AI, involves systems learning from structured data through neural networks that replicate the human brain’s structure. 

A prime example of AI in the broadcast was during the FIFA World Cup 2022 in Qatar, where AI tracked players and ball positions in real time, enhancing decision-making and broadcast accuracy. Twelve dedicated tracking cameras under the stadium roof tracked the ball and up to 29 data points of each player, 50 times per second, calculating their positions in real time. An inertial sensor in the balls provided data combined and mapped onto a 3D model, used to assess offside calls and other decisions.

AI in Broadcast and Films

There is an unprecedented increase in AI and ML technologies in the media and entertainment industry. Much of its market growth is due to the popularity of virtual assets like high-definition graphics and real-time virtual worlds. AI offers enormous benefits to broadcasters by simplifying content management workflows, providing everything from voice-controlled EPGs to real-time, high-volume content analysis. Since content analysis is central to broadcaster business models, AI metadata and speech recognition improve the discoverability of older archive content. 

Automated tagging, facial recognition, and contextual object recognition have simplified workflows for tasks like brand exposure tracking. This growth has led to the expectation that AI in the media and entertainment industry will become a $99.48 billion business by 2030, according to a new report by Grand View Research Inc.

See detailed report here : AI In Media & Entertainment Market Growth & Trends

AI and Broadcast Graphics – Virtual Worlds

Creating functional workflows isn’t the only interest for broadcasters. Establishing AI-powered virtual studios is a powerful motivation. Using tools like Epic Games’ Unreal Engine, broadcasters can create entire virtual worlds in real-time. Hakan Öner, Business Development Manager for Nordics and DACH at Zero Density, explains that AI allows broadcasters to visualize and create engaging content. 

Vizrt CTO Gerhard Lang emphasizes that storytelling, supported by data and new content presentation, is crucial for engaging viewers and making impactful broadcasts. "For the producers, having an opening and catching the viewer’s attention of course is super important," says Lang. "But the whole thing needs to be functional. You need to tell a story. No matter whether this is a news show or a sports show, people will focus on how you present the content, and how you explain what was happening. In the end, data is king so how can you present the data or bring in new content? Those are the areas that are crucial for producers and where we get the most requests.”

How AI is Transforming Broadcasting

AI’s implementation in broadcasting leverages producers with analytics, helping them make better, more informed decisions. AI-powered analytics assist broadcasters in gaining insights into their business and making data-driven decisions. The technology helps broadcasters gather data from various sources and evaluate it in real-time. For example, broadcasters can use AI to analyze viewer behavior, gaining insights into engagement levels and making informed decisions about content, its type, and suitable air times. This increases program ratings and revenue for broadcasters.

Conclusion

AI is significantly impacting the broadcasting industry. We are seeing a surge in AI and machine learning usage to enhance storytelling and live broadcasts. AI can generate graphic visual effects in real time, boosting the overall visual appeal of broadcasts. 

As a broadcaster considering AI technology, MediaGuru AI Services, an end-to-end service provider to broadcasting companies, can be the right choice for AI implementation in your Broadcast ecosystem. MediaGuru specializes in crafting broadcast centers from scratch and delivers cutting-edge technology to meet broadcast needs, helping maximize viewer engagement and retention.