Technology is now an integral part of the entertainment industry. The proliferation of streaming platforms has permanently changed the traditional entertainment business model. Audiences are prioritizing convenience and personalization. Artificial intelligence (AI) and machine learning (ML) can empower entertainment businesses by transforming how content is discovered, marketed, and consumed.

Streaming platforms now provide users access to vast content libraries. However, users often struggle to make decisions about what content to watch. It can be challenging for users to determine if a piece of content is worth watching. AI allows streaming platforms to tailor content recommendations to user preferences. It can analyze historical content viewership data to determine which types of content resonate the most with customers. Improved content recommendations can improve the user experience and increase content discovery by new audiences. Furthermore, AI recommendations continue to improve as user viewership and preferences change over time.  

Audiences have access to more content than ever before. AI-driven search optimization ensures users find and discover content produced by entertainment companies. It can optimize text, visual, and voice search, and it can help content rank higher on search rankings. Furthermore, it can help categorize content and associate it with relevant search terms to drive content discovery. Optimization can cost-effectively expand the reach of different types of content, it can also reveal opportunities for advertising, partnerships, and collaborations.  

Marketing upcoming and released content is an expensive endeavor in the entertainment industry. Machine Learning can detect patterns in audience data and generate insights on demand, preferences, and market trends. ML can help businesses understand what’s most important to different audiences and which variables impact their decision to purchase or consume content. It can identify behavioral patterns and categorize them into segments based on shared characteristics. The ML insights enable marketing teams to build a targeted strategy to maximize the impact of marketing activities on audiences. Furthermore, AI tools can autonomously adjust the marketing campaign content, duration, and distribution of campaigns across advertising platforms based on audience preferences. 

Content streaming platforms have increased access to international content. Streaming companies face the challenge of creating subtitles for content in multiple languages, which requires extensive translation and proofreading. The costs of subtitle generation can quickly accumulate as streaming services introduce more regional content. ML-powered translation systems can intelligently produce subtitles in several languages by recognizing human speech from sound and video data. They can learn to interpret sentence structure, vocabulary, grammatical structure, regional nuances, etc. Furthermore, ML algorithms can synchronize subtitles based on content to reduce issues that may negatively impact the viewing experience. 

Modern audiences actively voice their opinions through discussion threads, comments, likes, shares, etc. ML can help businesses collect and interpret all this information spread across social platforms to gauge performance and audience reactions. Sentiment analysis can determine the audience’s emotional state based on their responses. They can also help evaluate specific aspects of content that customers may like or dislike, which can help make decisions on future content development. Furthermore, it can alleviate the burden of traditional review analysis, which can be tedious and time-consuming.