The Transformative Power Of Generative AI In The Media & Entertainment Industry

Executive Summary The Media and Entertainment (M&E) industry continues to rapidly evolve as new technologies redefine how content is created, consumed, and monetized. Generative AI (GenAI) is at the forefront of this transformation, producing opportunities and challenges for traditional back-office operations, primary media processes and business functions.

This article explores how media companies can leverage GenAI opportunities while strategically managing associated risks. Key takeaways include:

1. Generative AI in the Media Industry: New technologies are transforming the manner in which we create, consume and interact with media content. This shift is changing traditional back-office operations as media companies evolve into digital businesses, while digital-first companies are expanding into media.
2. Content Creation Processes: By using GenAI, companies can now produce large volumes of content by automating some aspects of content creation and curation. This technology provides insightful suggestions for human creators and assists in writing, editing, brainstorming, and creating visuals, among other tasks.
3. Licensing and Monetization: As Large Language Models (LLMs) are training on web content, copyright and intellectual property infringement are an imminent risk because the content they generate may be similar to existing brands' tone and style. On a positive note, media companies can license valuable content to AI companies for LLM training, opening new revenue streams.
4. Original and AI-Generated Work: As AI improves in content creation, it becomes harder to distinguish between original and derivative works, introducing new challenges regarding intellectual property rights. However, GenAI also provides new opportunities such as revenue generation by reviving established content franchises with AI-assistance.
5. Content Distribution: GenAI has reduced the time to regionalize and distribute content, expediting the content production lifecycle, and allowing for dynamic, personalized iterations tailored to regional or demographic preferences.
6. Personalized Advertising: GenAI optimized-data and predictive analytics enable highly personalized and more effective ad campaigns. Media companies should leverage algorithms and test campaigns at a more strategic level while providing users the ability to manage ad preferences and data privacy.
7. Genuine and Fake Content: As GenAI becomes increasingly sophisticated, users are finding it harder to distinguish genuine from fake content, leading to heightened skepticism among audiences about the authenticity of content. This pushes an even higher burden on media companies and publishers to establish trust and credibility.

The Transformative Power of Generative AI in the Media Industry

New technologies are transforming the way consumers create, consume, and interact with media content. As companies adopt these innovations, many industries have developed media capabilities, leading to an overlap with the M&E industry. This shift is changing traditional back-office operations as media companies are evolving into digital businesses, while digital companies are expanding into media. This has led to increasing competition for key media revenue sources like content, advertising, and subscribers. As such, media companies are particularly vulnerable, creating the need to protect their market share and adopt digital-first strategies. While GenAI has heightened the urgency for media companies to transform, it has also accelerated their evolution and boosted their competitiveness against technology companies.

Particularly, the use of new technology has brought traditionally consumer-distant media companies closer to their audience. Technology, including GenAI, has brought significant advantages to companies, such as the quick production of large volumes of highly personalized, quality content and the reduction of labor time and costs through the automation of some aspects of content creation. However, with these opportunities, there are associated risks and challenges. For instance, as audiences are becoming increasingly skeptical about authenticity, media brands now risk negative user sentiment and perception, which may lead to issues like lower engagement, among others.

In this article, we discuss how GenAI impacts all areas of media, from content creation to distribution and audience engagement. We also provide recommendations on how to capitalize on these changes.

Revolutionizing Content Experience

GenAI technology gives subscribers more personalized, engaging, and interactive content. For example, users can now interact with GenAI through interactive dialog that retains the context and continues the discussion in a human-like conversation. AI models have the ability to generate responses based on the user's input, making it possible for users to solve problems, request specific content, and make transactions, among other actions. A great example of this type of content isBlack Mirror: Bandersnatch, an interactive science fiction film in which viewers make decisions for the main character. Another example isAmazon Prime's X-ray feature, which helps viewers access information about actors, soundtracks, production details, and bonus content.

What is the impact on media companies?

Enhanced personalization and interactivity keep audiences on platforms for longer periods, reducing churn rates and providing deeper insights into user preferences through predictive analytics.

Streamlining the Content Creation Process

GenAI is revolutionizing content creation and enabling high-volume, quality content by assisting in tasks across all the stages of production, from ideation, scriptwriting and editing to visuals and special effects. For instance, The Washington Post developed Heliograf, an AI-powered tool that generates real-time news reports, whileAlibaba uses AI to create product descriptions for its e-commerce platforms.

What is the impact on media companies?

By using GenAI, media companies can produce large volumes of engaging, quality content targeted to specific audience segments with reduced effort. If used effectively, this approach can save time and reduce labor while allowing human creators to focus on higher impact content production activities.

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20 August 2024

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