How is AI Helping Broadcasters Meet the Demands of Modern Sports Fans

On-demand media and personalized content have had a tremendous impact on the entertainment industry, particularly sports broadcasting. With sports fans’ increasing desire for access to short, concise and high-quality content from the convenience of their mobile screens, college major sporting leagues including the NFL, PGA Tour, NBA and the Champions League have begun to live-stream their events over social media and other internet sources to satisfy their growing mobile audiences. It’s no wonder. A 2022 survey from HubSpot revealed that short-form video has the highest ROI of any social media marketing strategy, which is why 51% of marketers use it. Further, a senior media analyst for Vanity Fair conducted a survey and found that about half of young fans surveyed prefer highlights over a live sports broadcast compared to older generations.

Well-done highlights, which last for about 5-10 minutes, present a narrative that summarizes the sporting event adequately without having to go through the entirety of the content. While this is great for sports fans, it is no easy task for broadcasters using traditional editing methods, which rely heavily on time-consuming manual (human) processes that cannot keep pace with the expectations of today.

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Manually sifting through raw footage and extracting specific moments to produce these highlights instantly requires large teams. Given the high volume of footage each broadcaster compiles on any given event day across the many events, there’s a lot of content to process. That’s precisely why new technologies, including artificial intelligence (AI) and deep machine learning (ML) algorithms, are becoming game-changers in sports broadcasting. When only a small number of events and moments of brilliance are classifiable as highlight-worthy, an AI model can increase team efficiency by reducing manual effort and time lag, leaving the entire production team with more time to focus on producing high-quality material.

Companies investing in these new technologies are keeping viewers engaged and fulfilling their desire for instant content delivery while simplifying the video editing process and reducing overall costs for broadcasters. Take Formula One (F1), for example. F1 is among the most exciting sporting events in the world with a global audience of 445 million viewers across the globe. With 20 racers competing in 23 races across the globe, it offers both amazing opportunities for the sports content itself as well as content related to the countries where the races are held. This year, races will take place in some of the most captivating locales, from the United Kingdom to the United Arab Emirates, offering a very diverse geographical and cultural mix of viewers.

While linear broadcasters have the advantage to acquire the most valuable media rights, emerging over-the-top (OOT) platforms such as Amazon Prime Video, Facebook Watch, YouTube TV and Netflix are growing in their respective markets, challenging the status quo through the implementation of AI and ML technologies to create shorter snackable content pieces. To compete for audience share, traditional broadcasters need to foray into short-form content; more so during mega sports events like the F1, which may include long intervals before a highlight occurs.

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With content contextualization and next-generation metadata management, AI has the power to transform the way content is rendered by broadcasters for consumption. AI cognitive technologies like vision models, optical character recognition, audio detection, facial recognition, spatial awareness and object recognition, in particular, significantly increase the quality of metadata that can be captured and simultaneously provide results free of human error using purely automated techniques.

Considering the explosive growth of digital sports video content, there’s no better time than now for broadcasters to take charge of content archives and make it work harder for them. There are many AI and ML platforms on the market. Starting with a demo is one of the best ways to discover which suits the most needs and requirements. Ask for case studies or other resources that reflect return on investment. And finally, choose a partner that’s trustworthy, intelligent and willing to collaborate.

[To share your insights with us, please write to sghosh@martechseries.com]