7 Use Cases for Generative AI in Media and Entertainment

We spend much of our lives being entertained by media, whether we’re watching the latest superhero movie, scrolling through YouTube, or conquering the final boss of a video game. And increasingly, we want personalized experiences. With generative AI in media and entertainment, content can be dynamically generated and tailored to a degree previously unimaginable.

Enterprise companies spent over $19.4 billion on generative AI in 2023, and they’ll more than double that total this year, according to IDC. Entertainment and media companies are no exception, as they look to capture consumer attention and explore use cases for generative AI.

Let’s explore some of the use cases for entertainment and media companies, including immersive virtual worlds, AI-generated music, and personalized storytelling.

4 Benefits of Generative AI in the Entertainment Industry

Generative artificial intelligence (AI) isn't just a passing trend; it could reshape how we think about entertainment and media. This technology will affect how media is created, consumed, promoted, and experienced. 

Generative AI can empower creators, producers, and consumers alike by offering unprecedented levels of personalization, creativity, and efficiency. With generative AI, one-size-fits-all experiences are a thing of the past. Consumers, with the help of entertainment companies, will be able to curate their entertainment based on user-specific preferences and interests. 

As this nascent technology takes hold, many companies are asking questions about generative AI, its potential benefits, and where to best deploy it. Here are four ways generative AI will help media and entertainment companies work more efficiently and connect with audiences in new ways.

Accessing Deeper Audience Insights

Generative AI helps content creators of all sizes gain a better understanding of audience preferences, trends, and patterns. This data, rapidly analyzed by AI, can help entertainment and media companies determine what new content to make or how to tailor their offerings to specific demographics. 

For instance, a streaming service could use generative AI to ask questions about their audience using natural language processing, generating real-time responses about content preferences, interests, and suggestions for future projects. 

Reimagining the Creative Process

Generative AI can support and supplement the human creativity already abundant in entertainment and media across formats. The potential for time, cost, and labor savings, especially in rote processes, is huge.

Generative AI tools can add value throughout the creative process, starting with early stages such as storyboarding and script outlines. For example, an AI tool could generate storyboards based on a prompt template, or it could review existing storyboards and discern recommendations for framing, composition, and visual storytelling.

Later in the process, generative AI tools hold promise for adding visual effects, assisting with music composition, or editing and replacing recorded dialogue. As text-to-video capabilities continue to improve, these opportunities will only grow.

Transforming Content Delivery and Consumption

Companies are leveraging generative AI to churn out high volumes of content across different channels and contexts, including social media, video, and long-form text. The potential for AI is to scale up volume, preserve quality, and expand the targeting of key consumer audiences. 

Companies using generative AI are already meeting customer content demands 66% of the time, according to research from Deloitte Digital. Companies not using generative AI score more than 20 percentage points lower.

Providing Immersive and Interactive Experiences

Entertainment and media companies are already using virtual reality (VR) and augmented reality (AR) technologies, and generative AI can make these efforts more seamless and successful. 

For example, AI tools can help users create digital avatars that mirror their physical appearance and replicate their mannerisms and behavior. This level of realism and personalization adds to the immersion and interactivity of VR/AR experiences, making them more engaging and lifelike.

In the metaverse, media companies can use generative AI to create enthralling experiences that blur the lines between fiction and reality. One potential result of this approach is a VR storytelling experience where humans mingle with AI-generated characters. These AI characters will respond to questions, engage in conversations, and even adjust the storyline based on user choices.

7 Ways to Use Generative AI in Entertainment and Media

There’s a rapidly growing number of use cases for generative AI in entertainment and media. Let’s explore seven ways these companies are incorporating generative AI into their businesses.

Content Localization

Content localization refers to the process of adapting and translating content to different languages, cultures, and regions. This process involves companies translating text, creating dialogues, writing instructions, and providing localized voiceovers, among other services. 

MagellanTV, for example, uses generative AI to internationalize its content library of streaming documentaries. Most of the company’s content was created in English, but AWS services including Polly, Transcribe, and Translate help create an automated dubbing and captioning pipeline.

Content localization is especially important in the gaming industry. Generative AI can help video game makers break down language barriers and create more inclusive gaming experiences — and do so more effectively than less automated efforts. Localization can also improve player immersion during gameplay, leading to increased engagement, retention, and loyalty. 

In-Game Item Generation

Creating in-game virtual items, such as costumes and gear, historically has required extensive manual effort from a team of designers. Generative AI tools like Stable Diffusion and Runway are helping game developers drastically reduce labor hours while offering a wider variety of themes and item versions. 

These AI tools help developers continuously introduce new and unique items into the game, keeping it fresh and exciting for players. Players enjoy even greater possibilities for customization, improving the overall gaming experience. In-game item generation can also be lucrative — extending the game's lifespan and creating long-lasting revenue streams through microtransactions or downloadable content add-ons.

AI-Generated Games

AI-powered game creation tools, such as Unity Muse, are revolutionizing the development landscape. Smaller, budget-conscious dev teams can accelerate production without needing to hire additional staff. With intuitive interfaces and pre-trained models, there’s a lower barrier to entry than for many traditional game development tasks. This accessibility allows for rapid prototyping, testing, and refinement, improving speed to market and rewarding developers for their curiosity. 

For larger companies with hundreds of developers, designers, artists and engineers, projects that have traditionally taken years can potentially be completed in months. Generative AI can help these companies create characters, inventory and storylines automatically. Additionally, quality assessment processes such as testing, fine-tuning, and debugging can be greatly accelerated.

Digital Avatars and Characters

Digital avatars powered by generative AI can be a cost-effective alternative for creating and animating digital characters, as AI reduces the need for hiring professional actors. Companies are exploring the potential of generative AI to generate realistic and customizable avatars that can be used in movies, games, and virtual experiences.

Bespoke Video Production

Advancements in AI models make it possible to generate personalized videos starring individuals and even iconic figures from the past. While still in its early stages, this use case holds immense potential for creating unique and engaging video content, which could have a considerable impact on film and TV production. 

Entertainment and media companies will have to be careful about implementing AI into audio and video production. They’ll need to account for any legal requirements, including copyright law and union contracts. But in the long run, generative AI could drastically reduce the time, money, and human staffing required to make video content across formats.

Audiobook Generation

AI-powered text-to-speech technology could help publishers publish audiobooks without the time and expense of human voice actors. This technology can also give authors more options when they’re searching for the perfect voice to narrate their works.

This cost-effective approach allows publishers to convert a wider range of books into audiobooks, including those previously considered financially unviable. As a result, literature and nonfiction have become more accessible for audiophiles.

Personalized and Automated Marketing

Entertainment and media companies can improve their marketing strategies by incorporating personalized and automated approaches. Integrating generative AI with AWS services such as SES (Simple Email Service), Pinpoint, Kinesis, and Lambda enables brands to create profiles, personalize content, and improve marketing automation based on real-time customer sentiment. This seamless integration allows companies to tailor their marketing messages based on individual customer preferences, behaviors, and interests.

Turn Your Generative AI Concept Into Reality 

Generative AI in the media and entertainment industry is here to stay. Companies that embrace this technology will be able to produce unique and valuable content more efficiently than ever before. However, as with any emerging technology, there are still many unknowns regarding generative AI. Entertainment companies will need to implement the right tools, mitigate risks, and monitor consumer sentiment as they roll out generative AI. To do this successfully, they’ll need a trusted and experienced partner.

As an AWS Premier Tier Services Partner, Mission Cloud has a proven track record of working with companies across industries to develop generative AI solutions that meet their specific needs. With in-depth experience and technical expertise at your side, you can successfully move your projects from ideation to deployment. 

If you're ready to turn your generative AI concept into reality and revolutionize your media and entertainment offerings, get in touch with a cloud advisor at Mission Cloud today. They'll work closely with you to understand your unique requirements and develop a tailored generative AI solution that aligns with your business goals.

FAQ

How are intellectual property rights managed when generative AI is used to create or modify content, especially when the content might resemble existing copyrighted works?
Managing intellectual property rights in the context of generative AI involves navigating complex legal frameworks often not fully adapted to the nuances of AI-generated content. Creators and platforms typically use a combination of copyright law, licensing agreements, and new policies specifically designed to address the challenges posed by AI. This includes determining the ownership of AI-generated works and ensuring that such creations do not infringe upon existing copyrights, which may require innovative approaches to copyright law and content licensing.

Can generative AI adapt to rapidly changing trends in media consumption, and how does it incorporate audience feedback to improve future content creation?
Generative AI has the potential to rapidly adapt to changing trends in media consumption by analyzing large datasets to identify emerging patterns, preferences, and feedback from audiences. This adaptability allows the creation of content that resonates with current trends and audience demands. Moreover, incorporating audience feedback into the AI's learning process can further refine and improve the relevance and appeal of future content, making generative AI a powerful tool for dynamic content creation aligned with consumer preferences.

What technical challenges do companies face when integrating generative AI technologies into their existing production pipelines?
Integrating generative AI technologies into existing production pipelines presents several technical challenges, including significant computational resources and integrating AI tools with traditional content creation software. Additionally, companies must address data privacy concerns, ensure the quality and authenticity of AI-generated content, and manage the potential impact on human creators' roles. Overcoming these challenges requires a careful balance between leveraging generative AI's capabilities and maintaining the integrity and artistic value of the content.