Artificial Intelligence: when media and entertainment reinvent creation and information

Artificial intelligence is profoundly transforming the world of media and entertainment. In the news industry, information circulates faster than ever, and companies must continuously analyze their data to remain credible in the eyes of a demanding audience. In the entertainment industry, studios are experimenting with new solutions to improve production and deliver unprecedented experiences to their clients.

Generative AI acts as a catalyst: it helps produce new content, identify trends, reduce costs, and improve quality. But it also raises questions: who controls the use of data? How can intellectual property be preserved in a world where information is omnipresent online? And above all, how can we ensure these technologies serve both the media and their clients, rather than threaten the work of journalists and creators?

3 Examples of Strategic Partnerships and New Business Models

Financial Times: One Agreement to Govern Its Information
The Financial Times chose to anticipate the rise of artificial intelligence by signing an agreement with OpenAI. Its information, drawn from archives and recent articles, is now accessible in ChatGPT with clear attribution. This choice illustrates a clear strategy: to enhance the value of journalistic data and provide clients with controlled access to quality content. Analyzing this move shows that media companies want to transform information search into a genuine revenue source.

News Corp: Leveraging the Media’s Legacy
With News Corp (Wall Street Journal, The Times, The Sun), an immense news database becomes a resource for artificial intelligence. By granting access to its archives for model training, the group demonstrates that concrete solutions exist to monetize information. For its clients (readers, subscribers, partners), this strategy ensures that journalism continues to be funded. Here, artificial intelligence is not a threat: it becomes an innovative way to analyze and enhance collective memory.

Vox Media: Smart Content and Marketing
Vox Media adopted a hybrid approach. The company is not limited to licensing its information: it is testing new solutions that combine editorial content and marketing, particularly in online affiliation. Generative models are used both to analyze data and to create commercial formats better suited to clients. This search for balance shows how media can broaden their business model through AI.

These partnerships show that media companies are seeking to transform their information into strategic assets. But beyond data governance, artificial intelligence also paves the way for new editorial formats and personalized user experiences.

3 Examples of Editorial Transformation and Immersive Formats

BBC: Personalizing the News
The BBC created a “Growth, Innovation and AI” department to make better use of generative technologies. The goal: personalize information for its clients, analyze consumption habits, and offer solutions tailored to different audiences. In a world saturated with news on social networks, a media outlet’s ability to research, analyze, and quickly disseminate relevant information becomes a decisive advantage.

BloombergGPT: A Proprietary AI Model
Bloomberg launched BloombergGPT, a large AI model trained specifically on financial data. It allows economic information to be researched and analyzed with unprecedented precision. This decision to integrate the technology in-house illustrates the desire of some media outlets to control their own tools rather than depend on external solutions such as Google. For its clients, Bloomberg provides information that is analyzed, contextualized, and enriched by artificial intelligence, without sacrificing editorial quality.

TIME: Immersive Audio News
TIME transformed its newsletters into AI-generated audio briefs, delivered by two realistic synthetic voices. Each piece of content explicitly cites the journalist behind the information, ensuring intellectual property and transparency. For TIME’s clients, this immersive and crafted format makes it easier to consume news, particularly on mobile and streaming. It is an innovative solution to capture an audience accustomed to switching between video, social media, and online news.

After media and their personalized information, entertainment itself is being transformed. In this sector, AI is directly at the service of creation and production, offering studios and clients renewed experiences.

3 Examples of AI-Assisted Creation and Production

Ubisoft: Automating Dialogues to Enhance Creativity
With its Ghostwriter tool, Ubisoft allows scriptwriters to automatically generate dialogues for secondary characters. This solution frees up working time and improves the narrative quality of games. By analyzing client feedback, AI also helps refine creation. This case illustrates how video game studios integrate generative models to optimize production without replacing the creative exploration of teams.

Square Enix: Large-Scale AI Strategy
Square Enix announced a massive strategy to integrate artificial intelligence into its production pipelines. The company aims to analyze audience needs in real time, test new narrative forms, and reduce development costs. For its clients, this means more immersive and personalized experiences. This decision shows how a major entertainment company can turn the use of AI into a true growth pillar.

Flawless AI: Films Adapted into 10 Languages at Lower Cost
The startup Flawless developed an automatic lip-syncing technology. A film’s dialogues can be translated and adapted into multiple languages while staying perfectly aligned with the actors’ lips. Deployed on the film Venom: The Last Dance, this solution drastically reduces costs and opens access to new markets. For studios as well as clients, AI becomes a key tool for international distribution and quality experience.

AI-assisted production proves that solutions exist to create faster and better. But entertainment is not only about production: it is also about rethinking the client experience, reinventing emotions and shows.

3 Examples of Immersive Experiences and Enhanced Emotions

Lucasfilm: The Voice of Darth Vader
Lucasfilm collaborated with a voice-cloning startup to recreate Darth Vader’s voice in the Obi-Wan Kenobi series. This work of vocal research and analysis shows how AI can extend the artistic life of an iconic character. For clients, it is a powerful emotional experience, but for the industry, it raises questions about rights and intellectual property.

Top Gun: Maverick: Recreating Val Kilmer’s Voice
In Top Gun: Maverick, AI made it possible to recreate Val Kilmer’s voice, affected by illness. This technical feat offered the film’s clients a unique moment, where technology and emotion converged. This case shows that AI is not only a production solution: it can analyze old sound data to restore a human and sensitive experience.

Las Vegas Sphere: A Wizard of Oz in 16K
The Sphere project in Las Vegas, in partnership with Warner Bros and Google DeepMind, illustrates the ultimate ambition of augmented entertainment. Thanks to generative models, The Wizard of Oz was recreated in 16K, projected onto a monumental dome with drones and immersive sound. Clients are no longer mere spectators: they live a total sensory experience. This solution demonstrates that AI can analyze cultural heritage, transform it, and amplify it for the entertainment world.

From journalism to blockbusters, from information research to artistic creation, artificial intelligence now permeates all media and cultural industries. But it also brings new collective challenges.

Between Innovation and Responsibility

Artificial intelligence opens up unprecedented opportunities for media and entertainment: better data analysis, new economic solutions, enhanced client experiences, accelerated creation. But it also raises crucial questions: how to regulate the use of information, protect intellectual property, and guarantee content quality in a world saturated with networks and platforms?

Current research shows that the future of the sector will depend on balancing innovation and responsibility. Media companies must analyze their practices to avoid losing public trust, while entertainment companies must find solutions that respect creators’ rights. Clients expect rich and personalized experiences, but they also demand reliable and transparent information.

Ultimately, artificial intelligence is not just a technical tool: it is redefining how media produce and distribute information, how studios create and share content, and how clients experience news and entertainment. The real question, therefore, is: will we know how to use this technology to enrich the human experience, rather than reduce it to mere automated production?