AI and machine learning make inroads in broadcast – but ROI will have to be seen in 2021
If 2021 was the entire year when AI/ML (artificial intelligence and machine learning) took off in video production, then 2021 has to be the year the industry begins to see some payback- otherwise it may go the clear way of other recent 'flash in the pan' tech trends like 3D and VR.
That is not likely considering that AI/ML – regardless of how you slice the definition – isn't a niche product but a worldwide tool for vendors to build up media specific applications. According to the IABM's latest bi-annual Buying Trends survey, which tracks technology trends, actual AI/ML adoption within the broadcast and media market is up from 2% to 13% in just six months from April to September this year.
The survey data implies that it is larger organisations which are more likely to deploy AI technology, with adoption varying across different segments from the content logistics. Another 68% are most likely or very likely to deploy it within the next 2-3 years.
While broadcasters are undoubtedly tinkering with AI/ML tools to automate and augment current workflows, as one unnamed broadcaster told the IABM, \”The challenge is monetising it, or creating real commercial value\”. In other words, the use of AI/ML demands a genuine business case, otherwise costs can easily escalate to outweigh any potential advantage.
Alongside the cost/benefit equation, there's also other challenges that may prevent media companies from taking full advantage of AI/ML. Namely, it's best suitable for working with large amounts of data.
\”While subscription-based broadcasters and media companies curently have significant viewer data to work with, FTA [free-to-air] broadcasters who are getting into OTT need to build new data to better understand their customers; this is why the uptake is slower of computer might be,\” infers IABM CEO Peter White. \”Other challenges relate to data management [i.e. training, and updating the data] and knowledge gathering. Also, media companies have to manage various kinds of data together in a single pool – avoiding data silos – to create real value from AI/ML algorithms.\”
IABM expects AI/ML adoption to increase in 2021 as current solutions mature and broadcasters build their databases, enabling them to drive more automation and liberate resources within their organisations. There's definitively an increasing interest in the numerous potential applications of AI/ML, however this is tempered by an overriding need – as with any new technology – to prove its business value.
The trade body, addressing the interests of apparatus manufacturers, also charted a slight rise in adoption of IP technology within the production sector this year. A good example of this trend is UHD production: IABM data shows that companies that plan to proceed to UHD are much more prone to purchase IP technology because of its format independence.
IABM does realize that most broadcasters possess a cautious culture that's holding back transition. \”Many broadcasters happen to be reluctant to abandon SDI and also have so far been inclined to consider a 'wait and see' approach,\” notes White. \”Maybe the floodgates are now beginning to open.\”
The finalisation of the SMPTE transport protocol ST 2110 earlier this year has given IP roll-out an uptick. But this is a slow burn. As the IABM underlines, \”IP not just impacts technical facilities and workflows, but the business and cultural environment.\”
From a cultural perspective, there is also a convergence between IP and broadcast that's very difficult to apply at traditional organisations. The move to IP is really as much about transforming culture as technology change.