The global media and entertainment industry is undergoing a transformation in the manner content is distributed. The prevailing ubiquity of content creation tools such as high-resolution cameras, content creation software and smartphones has enabled pretty much everyone to be able to create, publish and distribute audio, video and written content.
This growing trend has further accelerated by the global reach of the internet, which has seemingly become the replacement of traditional media instruments such as cable and radio with on-demand streaming services like YouTube and Netflix. As a result, consumers have a wide and diverse range of options to choose from in terms of media consumption.
Hence, media companies need to increase the quality and quantity of content they create in order to attract more consumers to increase their brand value. To help them reach this goal, media companies are turning to and becoming increasingly reliant on adopting technologies such as AI.
The utilization of Artificial Intelligence in the media and entertainment industry is enabling media companies to further develop their services and improve the customer experience overall.
Let’s look at a few prominent examples of AI in media and AI in entertainment that are significantly transforming the entire industry:
1. Metadata tagging:
Due to the exponential amounts of content created each minute, categorizing these items and making them easy to search and access for viewers becomes a very difficult job for media company employees. This is because the process involves watching videos and identifying objects, scenes or locations in the video to classify and add tags to.
To execute this task on a global scale, media creators and distributors are implementing AI-based video intelligence tools for analyzing the contents of videos frame by frame and detecting objects to add appropriate tags.
This technology is being leveraged by content creators or media publishing, hosting and broadcasting platforms to organize their media assets in a structured and accurate manner. As a result, irrespective of the volume, all the content created by media companies becomes easily accessible and searchable.
2. Content personalization:
Pioneering music and video streaming platforms such as Spotify and Netflix are experiencing massive success owing to the fact that they offer content that caters to all demographics, having varied tastes and preferences.
These companies are leveraging AI and machine learning algorithms to research individual user behavior and demographics to formulate recommendations of what they might be interested in listening or watching next, increasing their level of engagement. As a result, these AI-powered platforms are offering customers with content that suits their personal preferences, thus providing them with an incredibly personalized experience.
3. Reporting automation:
Supplementary to automating day-to-day or minute-by-minute operations, AI also enables media companies to execute strategic decisions. For example, leading media and broadcasting companies are leveraging machine learning and natural language generation tools to develop channel performance reports using raw analytics data.
Analyzing this raw data weekly, to gain and implement meaningful insights can be a daunting task for the analytics teams. However, by using AI-based data analysis and natural language generation-based reporting automation tools, business leaders can develop performance reports using easy to understand language commentaries, giving them accurate insights to carry out informed data-driven decisions.
4. Subtitle generation:
International media publishers need to ensure that their content is fit for consumption for audiences residing in different regions. To facilitate this, they should provide accurate multilingual subtitles for the video content. Manually writing subtitles for several shows and movies in several languages will require thousands if not hundreds of hours of translating for human workers.
Also, it may be difficult to procure the right resources to translate content for particular languages. Moreover, human translation also tends to be prone to errors. To navigate these challenges, media companies are implementing AI-powered technologies such as natural language processing and natural language generation. For instance, several video streaming platforms allow their publishers to automatically create closed captions for the videos uploaded on their platform, thus allowing the content to be more easily accessible.
To sum it up…
As competition and the growing need for efficiency continue to increase within the industry, the role of AI in media and entertainment is only expected to grow and develop further in the future. By exploring and experimenting with AI use cases mentioned above, media and entertainment companies are increasing their business performance potential by enhancing the user experience and entertainment value provided by them with increased efficiency.