Video, of course, is a very sensitive payload. Broadcast operations are mission critical and require 99.999% uptime. It is why the trend towards unified, automated processes has taken time to penetrate the broadcast industry. But AI/ML is maturing fast, and able to provide a force multiplier that permits fewer operators to manage very complex systems. NEW MARKETS, BIGGER WORKLOADS This transformation is essential for expanding the industry. End-to-end automation will enable broadcasters to scale up or down, to turn events on and off, and deliver experiences with different production values to various market segments. A broadcast of a tier three regional sport unique to certain US states needs to be handled differently, compared to an Olympics or World Cup.
Factor in new immersive and personalised AR/VR experiences, combined with granular monetisation models like ad targeting, and you can see how the complexities will overwhelm any broadcaster locked into inflexible systems. Take gamification, for example. It can range from free-to-play fantasy and casual games, to live micro betting. In the deregulated US, there’s been a huge spike in gambling revenues for sports, which is already valued north of $200 billion worldwide.* Major sports leagues are currently developing services that will enable fans to place real-time bets. Opening a sportsbook, you will need super-low latency, and it will have to be automatically run and regulated for the fail-safe efficiency it demands. This will be a form of robotic TV. Get ready to let someone else do the driving.
YOU CANNOT LINEARLY SCALE THE NUMBER OF BODIES REQUIRED TO MEET THE SOARING COMPLEXITIES OF PRODUCING AND DELIVERING CONTENT
* Statista.com, “Sports betting worldwide - statistics & facts”: statista.com/topics/1740/sports-betting/#dossierKeyfigures
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