Phil Eade, Senior Director of Media Platform Business Development, APJ, Ooyala, shares his thoughts on how AI can be a game-changer to Thailand's media industry. The full article can be found below:
According to IDC, global spending on artificial intelligence (AI) will likely cross US$46 billion in 2020. IDC also reported in 2017 that Thailand had the second highest number of organisations adopting AI amongst Southeast Asian countries.
AI has been adopted by Thailand's Ministry of Information and Communication Technology to implement services and tools that facilitates information sharing and collaboration, and supports decision making and problem solving. These initiatives have increased efficiency and brought about more personalised services for Thais.
While AI has been widely employed across industries, there are still many opportunities to be exploited for Thailand's US$14-billion media and entertainment industry. Broadcasters and media firms in Thailand are facing efficiency challenges in terms of delivering relevant and personalised content to consumers. An Ooyala poll in December 2017 revealed that 7 in 10 Thai media executives indicated that their media operations are only minimally efficient or not efficient at all. Particularly, 25% of respondents highlighted the need to automate their entire operational value chain.
From the large amounts of data generated from the consumption of videos, AI can improve the management and delivery of content and automate operations. Beyond that, AI can deliver better insights to help media executives make informed decisions and develop sound strategies for their business.
Here are three things AI can do for content production.
1. Make worthy content
Content producers are in a race to make content that is original and creative for the consumer. More often than not, this process requires extensive reviewing of past content to gauge viewers' interest and avoid duplication of content at the same time.
AI makes it easier for the publisher or broadcaster to understand the consumer's specific preference and behaviour by leveraging machine learning. For instance, if User X watches Video A then clicks to watch Video B, we can infer that the likelihood of User Y wanting to watch Video B as well is high if he/she watches Video A. These patterns feed into a powerful neural network of decision-making which content producers could rely on to create personalised content for consumers.
Couple this with an AI-powered in-depth calculation, which tells content makers the type of content they should prioritise and spend their production dollars on instead. You'd be more empowered to make a calculated decision rather than on intuition or superficial assessment. Consider yourself deciding to go ahead with producing a family drama series as the last set was a success. However, once you've factored in the full production costs against your revenue and returns, you might realise comedies are more profitable instead.
2. Give content a re-birth
As a lot of money is being spent on producing a piece of content, the ability to make the most out of it is key. Localisation of the content to cater to each market's needs and relevance is one way and AI could help speed up the process. Tech giants like Microsoft, IBM have AI tools that makes it easier to transcribe or translate audio into other languages, so you can offer your content to new markets.
Leveraging existing content is also another way. We can almost always hear the same pain point from broadcasters or publishers: "I don't even know what I have in my archive at this point." Locating relevant footage to supplement a news bulletin or documentary often becomes a huge challenge for content companies as they sift through the vast amounts of video assets that sit in their archives, let alone monetise them. With AI, media organisations can index existing content with powerful metadata capture techniques, enabling them to easily identify and repurpose that archived content.
3. Monitor live events
The issue with live events is that there are a lot of moving parts and if one thing goes wrong, it could cripple the entire event. That also means that monitoring a live event and troubleshooting issues are typically performed in siloes, leaving media organisations in a fix as they try to accurately pinpoint and resolve issues. For example, AI could watch out for unexpected spikes in viewership during the live broadcast and alert companies immediately to add server capacity and prevent the event from crashing. This gives production companies the opportunity to monitor and troubleshoot more quickly and efficiently (sometimes even before they happen).
Never too late for AI
The benefits of AI are exciting. Streamlined workflows, increased efficiencies, and improved monetisation are all promises that could be very well fulfilled. Additionally, with Thailand becoming an increasingly mobile population, only media companies that can deliver content in various modes and formats in a timely manner will gain.
However, AI is still in its nascent stage and only picking up steam across sectors. While it would in the foreseeable future become more advanced and integral in our tasks, that does not mean that human participation would be forfeited. Ultimately, AI should play the role of a work-partner who would give insightful answers but it is still up to humans to make the right decision.