Top AI Trends to Look for in the Media & Entertainment Industry

The entertainment and media sector is undergoing a significant transition in the way media content is transmitted. An increased presence of content-generating technologies like content production programs, high-resolution cameras, and cell phones enables anybody to produce, post, and share textual, video, and audio content.

Because of this, media firms have to provide more and better content to lure as many people as possible into increasing their worth. Media companies are turning to cutting-edge technology like artificial intelligence (AI) to assist them in achieving this goal.

The usage of AI in the entertainment and media business allows media organizations to broaden and enhance their services and boost consumer experience. Here are some trends of how artificial intelligence (AI) is changing the media and entertainment industries:

Television and Film

Recommendation & Personalization of Content

Popular video and music streaming services such as Spotify and Netflix are thriving because they cater to a wide range of demographics and preferences in terms of the material they offer. 

These organizations utilize algorithms based on artificial intelligence and machine learning to analyze the habits and demographics of their customers to suggest content that will keep them coming back for more. 

Thus, AI-based platforms can provide clients with material tailored to their unique preferences, thus giving a more personalized experience.

Recommendation engines analyze consumer watching data, browsing histories, rating data, durations, dates, and the type of equipment a user is using to forecast what must be offered at that time. Great blockbusters such as Money Heist have resulted from these suggestions.

Metadata Tagging

Media companies' professionals have a monumental task in categorizing and making searchable the many pieces of content they produce every minute. To categorize and tag video clips, you must view them and define the objects, situations, and locations.

Media producers and providers like CBS Interactive use video intelligence solutions based on artificial intelligence (AI) to scan video content frame by frame and detect objects to add suitable tags.

Journalism

Automated Journalism/Robots Journalists 

There are countless cases of robot journalism. Good examples include Bertie, Heliograf, the Washington Post, and Bloomberg's Cyborg from Forbes. According to some factors and data gathered from the analysis, these robotic journalists could build narratives for football games.

To prepare for the 2016 Olympics, Toutiao (a Chinese news aggregation website) constructed an AI writing robot called Xiaomingbot. It is the most famous piece and got almost 50,000 views. Moreover, you can send out emails, acquire materials, and publish stories with the help of automation technology.

Lastly, to keep users engaged with their content, companies like Opinary employ data-driven polls.

Music

Music Recommendations

Apple Music and Spotify are now using machine learning methods to categorize their customers and present them with more relevant songs or playlist recommendations. First, music suggestion systems like Songza were introduced in the early 2000s. 

Natural Language Processing (NLP) scrapes details regarding songs and musicians from the web. It uses machine learning methods like Collaborative filtration for consumers and song categorization on these massive streaming services.

Using Neural Networks helps ensure that their AI system is developed with a variety of factors rather than relying solely on the streaming data of their customers.

AI creates & helps Artists with Song Generation.

These tools are now utilized more for amusement than for music, but their possibilities are expanding. AI-powered music writing tool Soundraw allows users to compose their songs by merging AI-generated phrases.

Gaming

Customer lifetime value prediction

It is becoming increasingly difficult for corporations to acquire new customers because the availability of smartphone games is outpacing demand. As a result, mobile game businesses are establishing large analytics departments. 

Estimating customer lifetime value (CLV) accurately enables organizations to bid more effectively, prioritizing high-spending customers above those who are unlikely to use the product.

Virtual Reality / Augmented Reality

AI and ML techniques are increasingly being employed to make computer opponents more interesting and challenging to defeat. Animators can build virtual reality (VR) characters using artificial intelligence (AI). It was not uncommon for games to incorporate computer opponents that used rules-based logic to compete with human opponents.

The esports sector is expanding, and spectator interest in professional competitions has increased. The inaugural ceremonies of esports competitions capture as much interest as the Olympics, if not more, and the statistics back up this claim. 

The 2016 Rio Olympics opening ceremony was seen by 4.4 million people on YouTube, whereas 9.5 million people watched the 2017 League of Legends Worlds Inaugural Ceremony.

Gambling and Sports

Fraudulent Detection

Machine learning can assist internet gambling platforms in detecting fraudulent activities such as identifying theft or creating false identities, accounts farming, money laundering, and account takeover. On the other hand, SEON is a provider that employs artificial intelligence to verify the legitimacy of gamers.

CLV Predictions

It's common knowledge among casino management to offer special deals and perks to regulars and high rollers. Betting, like every other sector, has moved to the web. In 2024, the worldwide online gaming market is anticipated to be worth much more than $94 billion. 

With the help of artificial intelligence (AI)-powered analytics, gambling companies can better forecast their customers' lifetime value (CLV), allowing them to target special offers and promotions toward their most loyal customers.

Summing Up

Artificial Intelligence (AI) will play a growing role in the entertainment business as competition and efficiency demand rise. Entertainment and media organizations are maximizing their company performance by boosting the customer experience and entertainment quality offered by them with more effectiveness by studying and testing with the above mentioned and other AI use applications.

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