State of Play:
Exploring Generative AI‘sTransformative Effects on the Media &Entertainment Industry

PREAMBLE
Generative AI, or Gen AI, is a branch of Machine Learning,a subfield of Artificial Intelligence (AI), that involves training
a model to produce new data that is similar to given data. As
such, Generative AI can be used to create, edit, modify or
analyse content such as text, still and moving images, sounds,
and software code. With the models improving at a rapid
pace, new Gen AI tools are being rolled out into the market for
creators and businesses to use at an almost weekly cadence.
Nonetheless, the impact of this technology on the economy andsociety remains uncertain, with forecasts varying from modest
efficiency improvements to transformative business models anddiscussions about how governments and corporations can strike
an appropriate balance between technological progress andnecessary regulation.
In this White Paper, we aim to explore the state of play for
Gen AI in a selection of media and creative industries. We will
examine how media companies are experimenting with Gen AI
across their value chains to improve operations, create content,
and enable new services. We will also look at the differences inopportunities and challenges across different media sectors, suchas broadcasting, marketing, publishing, and recorded music. By
responsibly seizing these opportunities, we believe that Gen AI
can enable a new era of innovation and reshape these industries.
Media companies have long used AI to automate content
recommendation, personalization, and ad targeting. They
are now experimenting with Gen AI to create content more
quickly, efficiently, or in entirely new ways. Pre/Post production,
distribution, and marketing are being augmented by Gen AI, withintelligent personalization, conversational interfaces, and image
generation. There are a raft of AI partnerships being forged
between media companies and technology providers, both large
and specialized.

Preamble2

There are differences by media sector. Marketers are rapidly
embracing Gen AI tools, and AI offers clear opportunities there
for both efficiencies and new product offerings. Broadcasting,too, has many functions amenable to Gen AI augmentation.
While there are potential benefits to recorded music, they
are being embraced at a slower rate; publishers, meanwhile,
are proceeding very cautiously. The varying rates of progressoffer chances for knowledge exchange and learning from theexperiences of early adopters.
Looking ahead, there is the potential for entirely new products orbusiness models enabled by Gen AI in the media, such as fully
bespoke content made for a single consumer, user generated
tools that enable individuals to create substantial creative works
in short spaces of time, or newly interactive products.
The paper is structured into three chapters, each exploringa different aspect of Gen AI in the media and entertainment
industry. The first chapter explores into the current state ofexperimentation with Gen AI in the industry, highlighting how
media companies are using these tools to improve operations,create content, and enable new services. The second chapter
examines the foundational models of Gen AI and the interaction
between the media industry and both major and minor technology
providers. Finally, the third chapter explores the challenges anddebates surrounding the adoption of AI in the industry, and how
businesses are reacting to these issues. Through these threechapters, the paper provides an overview of the opportunities andchallenges presented by Gen AI in the media and entertainment
industry.

Preamble3

01

Exploring the State of Play:Gen AI Experimentationin the Media Industry

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

4Arthur D Little conducted (June-Sept, 2023) an extensive survey of the Media Industry
focusing on Gen AI cases, commissioned by Bertelsmann. It covered over two hundred
Gen AI models and applications spanning the entire Media Value Chain. Furthermore,
ADL observed over sixty technology partners, from tech giants to specialist providers,
ensuring a diverse perspective on the evolving role of AI.

2. Gen AI Models
Observed

1. Gen AI Use Cases

200+

3. Technology
Providers Assessed

200+

60+

LLaMa2Luminous

Figure 1. Arthur D. Little Gen AI study

The study examined a wide range of segments, including Broadcast, Entertainment &News, Music, Marketing, and Book Publishing, delving into critical sub-segments such as
content generation, instrumentation, creative collaboration, localization, sales chatbots,
marketing, and analytics.
The Broadcast, Entertainment & News sector emerged as a frontrunner in adopting
Gen AI for content creation, localization, and marketing. Meanwhile, the Music sector
concentrated on instrumentation, collaboration, and marketing, and Marketing exploredidea generation, analytics, and campaign/advertising placements. In Publishing, Gen AI
made strides in content generation and editing, language and localization, sales chatbots,and discovery.
Global media giants like WPP, Bertelsmann, Disney, Reuters, and Universal have quickly
grasped the potential of Gen AI tools, eagerly exploring their applications across diverse
media businesses. These players are forming dedicated task forces to unlock the fullpower of Gen AI across various segments.
Content

Localization

MarketingMusic

Instrumentation

Creation collab.

MarketingMarketingIdea generation

Analysis

Campaign

Publishing

Content

Localization

Sales chatbots

Broadcast

Figure 2. Analysis of Use Case Activity Across Media Industry Sub-Segments
N=160 cases (including Education) Source: Arthur D. Little Analysis

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

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We look at the four major segments of the Media & Entertainment industry:

1. BROADCAST, ENTERTAINMENT & NEWS
Content creation and production
Gen AI is used in automated script writing assistance, news and image generation.
Emerging applications like hyper-personalization and interactive storytelling are gaining
traction, with support from technology partners such as OpenAI, Runway, Midjourney,
and Synthesia.
Content creation

Post Production

Distribution and marketing

Automatednews generation

Voice cloning or generation

Ad personalization andaudience engagement

Reuters announced aprototype for an automated,presenter-led sports news
summary system in partnership with Synthesia
Arena Group Holdings,
incl. Sports Illustrated,partners with Jasper andNota AI to train LMs on its
archives for new stories

Netflix used Resemble’s
voice tech in “Andy Warhol
Diaries”
Respeecher was used forvoice de-ageing in Disney+’s“​​Obi-Wan Kenobi”, and forvoice cloning in Lucasfilm’s“The Book of Boba Fett”

Paramount Pictures used
Resemble AI to for a
personalized “Ghostface” callexperience
Warner Bros. leveraged
PhotoRoom’s API to createa “Barbie” selfie generator;
Photo-Room enabled theremoval of back-grounds atscale and integrated user
photos into Barbie movie
posters

Figure 3: News, Entertainment and Media Use Case examples | Source: Arthur D. Little

Post-production
Gen AI is being used for voice cloning, special effects and background alterations,content summarization and localisation (transcription, captioning/subtitling, automatedlanguage translation and dubbing). Industry players such as Disney, Netflix, and YouTube
are actively engaged in these advancements. They work with technology partners like
Runway, Resemble AI, Respeecher, and OpenAI. Bertelsmann is also in collaboration
with Papercup and ElevenLabs for subtitling and voice synthesis. ElevenLabs AIpowered audio fixing technology can help avoid days of reshoots or automated dialogue
replacement recording.

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

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Distribution and marketing:
Key players like NBCUniversal (Comcast), Paramount, Sony, and Warner Bros. are using
Gen AI to create engaging marketing campaigns, especially in tandem with film launches(see Figure 3).

Figure 4: Screenshot from „Stars on Mars““Stars on Mars“: Fremantle‘s Eureka Partners with Eleven Labs for AI-Enhanced
Localization Fremantle‘s Eureka collaborates with Eleven Labs to revolutionize the postproduction and localization process using generative AI for dubbing, voice synthesis, andtranslation.
This cutting-edge technology streamlines post-production by minimizing reshoots,
shortening production time per hour, and eliminating the need for voice actors to bepresent in the studio for looping, where actors re-record their lines while watching theoriginal footage, synchronizing their speech with the on-screen lip movements.
Furthermore, it simplifies global post-production operations, as the post-audio
department is no longer required to be near the voice actors. Additionally, it reduces thenumber of dubs needed.

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

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News
Some news publishers have been experimenting with AI tools for some time, suchas the Washington Post‘s Heliograf, which uses natural language generation to write
news stories. The Associated Press now uses AI to generate earnings reports, freeing
up journalists to focus on more complex stories. Some of the most interesting news
applications concern distribution and marketing, such as the Financial Times using AI tohelp readers find articles related to any highlighted text and making paywalls specific tothe content a potential subscriber is trying to access and read.

Figure 5: Bertelsmann Case: AI powered Newsroom n-tv.de

RTL Group: AI powered Newsroom n-tv: The newsroom of the future is poised to
revolutionize journalism by harnessing the power of GenAI to generate news content in avariety of formats for all media types. This innovative approach employs AI to identify themost compelling stories and customize news formats to suit the audience‘s preferences.
In a groundbreaking collaboration between RTL and partners, the ntv newsroom of
the future leverages cutting-edge algorithms to sift through a multitude of sources
and pinpoint the most relevant stories. The AI system then provides additional context,
uncovers missing information, and suggests related side stories to enrich the news
content.

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

8Furthermore, the AI technology assists in adapting stories to meet the specificrequirements of each media channel while maintaining the distinct style of the respective
brand. This ensures that the news content is not only engaging and informative but also
consistent with the brand‘s identity.
By using GenAI-driven content generation, the newsroom streamlines the news
production process and enhances the overall quality of journalism. This cutting-edge
approach paves the way for a more efficient and dynamic newsroom, capable ofdelivering timely and captivating news stories across various media platforms.
In addition to identifying and tailoring news content, the AI-driven newsroom can also
optimize the distribution of stories across different platforms, ensuring that the rightcontent reaches the right audience at the right time. This targeted approach leads
to increased engagement, higher viewership, and ultimately, greater success in thecompetitive news industry.
The newsroom of the future also has the potential to change the way journalists work,
freeing them from repetitive tasks and allowing them to focus on more in-depth reporting
and analysis. By automating the content generation process, journalists can dedicate
more time to investigating complex issues, conducting interviews, and providing uniqueinsights that enrich the news experience for their audience.
In summary, the newsroom of the future, powered by GenAI, promises to transform
journalism by streamlining content generation, enhancing the quality of news stories,
and optimizing distribution across various media channels. This innovative approach sets
the stage for a more efficient, dynamic, and engaging newsroom that caters to the everevolving needs of its audience.

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

92. MUSIC
Adapting IP and new IP Generation:
Gen AI has the potential to enhance creative aspects such as songwriting, music
composition, recording, editing, sound design, and post-production.
Universal Music Group has partnered with AI sound wellness company Endel.io to createfunctional, AI-generated music, repurposing artists’ music on their behalf. They have also
incorporated the AI music composition platform DAACI into their Abbey Road Studios.
Universal Music Group‘s partnership with social media music creation platform BandLabis aimed at promoting the ethical use of AI and the protection of artist and songwriter
rights.

Figure 6 Bertelsmann Case: CRO & Fenster

The inaugural BMG music video, entirely produced by AI, was developed in partnershipwith Sebastiaan Zimmerhackl, a trailblazer in German AI video production. Zimmerhackl
has collaborated with prestigious companies like Adidas, Google, and Universal since2018.
To craft this innovative music video, they employed the Gen AI feature developed by
Stable Diffusion and completed the video using After Effects.
The AI system examined visuals from CRO and 30 images supplied by his girlfriend,
Amanda, resulting in the captivating video.

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

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In May this year, Google released MusicLM, which is a text-to-audio tool to generatemusic, still in its infancy. Google is exploring a partnership with UMG to gain access tomusic to train the tool, also compensating rights owners for the use of their works.
More recently, Google DeepMind‘s Lyria, an AI music generation model, has introduced
two innovative AI experiments aimed at fostering creativity: Dream Track, a YouTube
Shorts experiment created to enhance connections between artists, creators, and fansthrough music production, and Music AI Tools, a collection of resources developed incollaboration with artists, songwriters, and producers to support and enrich their creative
processes.
While there is significant interest in Gen AI for music rights owners, the music industry
is still figuring out how to responsibly use Gen AI and also safeguard music rights fromunauthorised use.
Audience Engagement (Marketing)Streaming service Spotify stands out as a leading player here. It acquired Sonantic and its
AI DJ function to create custom playlists, to improve engagement and retention. Spotify
is also deploying Gen AI to create host-read ads for podcasts, aiding monetisation.
Music composition

RecordingMarketingMusic creation,
real-time generation

Voice cloning / generation

Music recommendation,
personalization

Universal Music Group
partnered with Endel toenable artists and labels
to create soundscapes fordaily activities like sleep

Google and Universal
Music are in talks tolicense artists’ melodies
and voices for songs
generated by AI: The
goal is to develop a tool
for listeners and fans tocreate tracks legitimately,and pay the owners of
the copyrights
Warner Music Group
have disclosed similarplans and talks with
GoogleSpotify has released
Spotify DJ, developedin collaboration with
its acquired voice techcompany Sonantic and
OpenAI: Spotify DJ isaiming at offering apersonalised listening
experience, delivering a
selection of music alongside AI-powered spoken
commentary about the
tracks and artists

Figure 7: Gen AI and Music | Source: Arthur D. Little

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

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3. PUBLISHING
Across the publishing value chain, Gen AI plays a role in content creation, content editing,and partially in design, layout, sales, and consumption. However, its adoption has so far
been slower compared to other industry segments like broadcasting. 2023’s Frankfurt
Book Fair made clear that there is widespread caution around deploying Gen AI in bookpublishing, though there was also an acknowledgement that attitudes could quickly
change.
Content Creation

Gen AI aids publishers in content creation, particularly in
writing assistance, and has promise for emerging areas
such as interactive storytelling. Publishers including
Hachette, Harper Collins, and Macmillan Education arepartnering with technology providers like OpenAI, Jasper,
and Google.

Content Editing/Adaptation Copy editing is a clear candidate for Gen AI efficiencies.
Gen AI is increasingly used for content adaptation,such as in the translation process, or turning books into
audiobooks using synthetic voice narration.
Sales and Marketing

Emerging use cases include automated sales chatbots
and content tagging. Penguin Random House isassessing new forms of marketing copy and design.

Figure 8: Penguin Random House´s BookBoost

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Penguin Random House´s BookBoost: BookBoost is a proprietary platform that leverages
first-party data, automation, machine learning, and AI to fully automate the process
for Facebook and Instagram advertising. This innovative tool helps to create, execute,and test advertising campaigns at scale with a focus on driving incremental sales andmarketing efficiencies. Results to date are very promising, with key metrics on par or
above benchmarks with strong performance in driving ad clickers to retail.
A BookBoost campaign starts when an opportunity is identified, for instance throughreal-time ‘buzz’ signals or on-sale dates. This triggers the creation of custom audience
segments based on various data points including content preferences and purchasebehavior and is followed by automated copy and image generation. For copy generation
the teams work with an AI platform called Copy.ai. The last part of the automatedworkflow is campaign set-up, with all elements required for a campaign pushed to theappropriate ad platform.
Before any BookBoost campaign is launched, the Ad Operations team reviews allelements of the campaign and communicates with marketers. Performance data is used
to optimize all elements of subsequent BookBoost campaigns, creating a virtuous cycleof improvement, and generating customized content that is highly relevant and appealing
to the target audience, encouraging its potential increased engagement with the texts.
Content creation

Sales and marketing

Automated writing assistance

Automated sales chatbots and content
tagging

Hachette Book Group is publishing an AI
poetry book titled ”I AM CODE: An Artificial
Intelligence Speaks”. The poetry collection
is written by code-davinci-002, an earlier
version of OpenAI’s ChatGPT
Harper Collins is using Jasper AI’s
copywriting tool to aid the publisher inrephrasing content, correcting the tone
through automated rewriting in theprocess

SAGE has partnered with Hum using its
Alchemist AI Engine to generate more
precise content tags on its large databaseof articles and journals
As a major online retailer, Amazon has
been using Generative AI to summarize
product reviews, including those on books,
to produce more targeted feedback toclients advising them on purchases

Figure 9: Publishing & Gen AI | Source: Arthur D. Little

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4. MARKETING
Across the marketing value chain, key players are eager to implement Gen AI to boost
efficiencies and enhance creativity.
Content Development, Editing, and Campaign Execution
Generative AI already plays a crucial role in rapidly generating ideas and images, evenautomating ad creation. Players including Omnicom and WPP are striving to develop andintegrate Gen AI solutions into their workflows. Omnicom has partnerships with key
technology providers like Microsoft, AWS, and Google, while WPP combines external
collaborations with in-house tools, developed in partnership with Nvidia. Agencies arefocusing on training custom models internally to safeguard client data.
Lead Generation, Customer Acquisition, and Reach Optimization
Gen AI can be used to target and personalise campaigns. Ads could show custom
images or copy depending on context or the target audience and iterate based on
effectiveness. Meta, Microsoft, and Google are working to integrate targeted and autogenerated ads into their search functions. WPP is tailoring marketing experiences fordifferent customer segments and efficiently localising ad content.

Content development and editing

Lead generation, customer acquisition,
reach optimization

Image, video, or voice generation

Targeted marketing

Omnicom’s BBDO is using Stable Diffusion for image-generation
WPP’s partnership with Nvidia will enable
WPP to generate creative elements via
Gen AI, e.g., integration of 3D content
creation for increased personalization
Stagwell’s Code and Theory uses Midjourney and Stable Diffusion for image
generation

Google plans to run search and shopping
ads inside its conversational AI via Search
Gen. Experience (SGE), enabling customers
to ask questions, receiving responses andautomated ads
Similarly, Microsoft is exploring putting
ads in the responses given by Bing Chat,its search agent powered by OpenAI’s
GPT-4

Figure 10: Marketing & Gen AI | Source: Arthur D. Little

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

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CASE STUDY
Revolutionising Media Industries: Stand-Out Example of Innovative Use Case for Gen
AI. We are already seeing innovative AI-powered tools and implementations in the media
industries.
One example:// Lip-Syncing Translation and Dubbing: Flawless AI‘s TrueSync technology is used to edit
content and create lip-synced versions of foreign-language films.

Source: Screenshot „Air Head“

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

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Creating video from text
OpenAI’s Sora text-to-video tool creates video clips in a range of styles from natural
language inputs. Selected creators have been given early access to the tool and havecreated experimental content. Film producers Shy Kids delivered impressive results intheir short, ‘Air Head’, about a man with a balloon for a head. This combined generated
clips with traditional post-production techniques like colour-correction, rotoscoping andsound design, but without the need for extensive CGI or practical effects that the concept
would otherwise call for.

Source: Screenshot Flawless AI TrueSync

Blue Sky Ideas vs. Limits
Beyond the limited integration of Gen AI tools into production, marketing and distribution,
we are starting to see bolder, albeit technically still limited, experiments that put
Generative AI at the heart of new media products.

01 | Exploring the State of Play: Gen AI Experimentation in the Media Industry

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“The Carnival of the Ages”// A fully AI-generated 90-second short, including narration// Made with DALL-E, Midjourney, Runway, and ElevenLabs// The filmmaker, Justin Hackney, claims that he “basically did it in 48 hours”

Source: Justin Hackney, YouTube

The newsroom of the future
In contrast to Bertelsmann, which works with long-standing partners such as Google andMicrosoft, other media companies have entered into various other partnerships:// Bloomberg uses NLG technology, Cyborg, to automate financial reporting// G/O Media is engaging in a Gen AI trial, which will produce stories for the publishers
AV Club, Gizmodo, and others// Channel 1 News is creating a personalised video newscast product// Ippen Digital Media uses Aleph Alpha for various newsroom tasks such as AI-assisted
headlines
Looking ahead, there are even more speculative concepts: whole new kinds of media
products, experiences and businesses, enabled by Gen AI. TV, books and marketing could
be interactive and personalised. Viewers could have agency over how a series ends, orreaders could converse with a character in a book. Music could be composed in real timein response to events in a listener’s day, generating a personal soundtrack to their life.
How far off, indeed how successful, these applications are likely to be is uncertain, but
the coming years will undoubtedly deliver some kind of breakthrough media application
powered by AI.

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02

The Technology Side of Things

02 | The Technology Side of Things

18The Gen AI landscape is rapidly evolving, with numerous models and technology
providers aiming to revolutionize creativity, problem-solving, and decision-making. Large
Language Models (LLMs) and diffusion models are at the forefront of AI innovation,offering powerful tools for various industries.
Key families of LLMs include GPT (OpenAI), Claude (Anthropic), Cohere Command(Cohere), PaLM and Gemini (Google AI). LLMs with open-source or other non-restrictive
licences, such as LlaMA (Meta), GPT-NeoX (EleutherAI), Jurassic-1 Jumbo (AI21 Labs),
Megatron-Turing NLG (NVIDIA/Microsoft), and Wu Dao 2.0 (Beijing Academy of Artificial
Intelligence), provide accessible options for researchers and developers.
LLMs can perform tasks like text generation, translation, summarization, question
answering, and code generation. They can help media companies personalize content,
generate insights, and create conversational interactive services.
For video and images, advanced diffusion models and image recognition systems,
such as Stable Diffusion (Stability AI), DALL-E (OpenAI), and Midjourney, can analyze
and produce visual assets. Proprietary models like Adobe‘s Firefly and Getty‘s Gen AI
tool (in collaboration with NVIDIA) offer image creation, editing, and advanced filtering
capabilities.
Emerging companies with targeted offerings like Persado (personalized marketing copy),
Synthesia (video creation platform using generative AI avatars), and Lumen5 (videos fromtext and images) are also gaining prominence in the media Gen AI space.
Based on ADL‘s evaluation of current media use cases, the distribution of activity andunderlying models was observed across various players, with a notable emphasis on
OpenAI, followed by Meta, and Stable Diffusion. (See Figure 11)

ModelsGPT4DALL-E 2

PaLM 2

Deep

Stable Diffusion 2

Midjourney v5.2 Composer

Lex

CohereMT-NLG
Command

GPT-3.5-turbo
LlaMa 2

Niji v5

Edify

Luminoussupreme

Figure 11: Popularity of LLMs
N=81, 2023 ADL Survey

02 | The Technology Side of Things

19

In summary, Generative AI advancements include:
1) Stable Video Diffusion for high-quality video generation, revolutionizing content
creation;
2) 3D scene inference from short videos, impacting TV, film, and gaming;
3) Large-scale multimodal models like Google‘s Gemini for seamless human-AI
interactions;4) Open-source mixture-of-expert models democratizing AI technology; and
5) Apple‘s MLX framework enabling smaller LLMs on end-user hardware, integrating AI
into everyday devices.

Technology solutions: Major partnerships between big tech & media companies
Major partnerships between big tech and media companies include:
NVIDIA and WPP are developing a generative AI-enabled content engine for digitaladvertising using NVIDIA Omniverse. This engine connects 3D design, manufacturing,and creative supply chain tools.
NVIDIA and Disney, Netflix, and WarnerMedia: NVIDIA is working with these media
companies to develop generative AI technologies for film and TV production, such as
generating realistic synthetic crowds, AI-powered video editing, and creating virtualworlds and characters.
OpenAI and media companies: OpenAI is working with the Associated Press, Netflix,and Adobe to develop generative AI technologies for journalism, personalized content
recommendations, and content creation tools.
Meta and media companies: Meta is partnering with NBCUniversal, Disney,
WarnerMedia, and Sony Music Entertainment to develop AI-powered tools for generating
realistic video, creating AR and VR experiences, and personalized marketing.
Google and media companies: Google is partnering with Fox Sports Interactive Mediaand Typeface to bring Gen AI to sports event broadcasts and develop marketing solutions.
Amazon and media companies: Amazon is partnering with media companies throughAmazon Web Services (AWS) and Amazon Studios to develop Gen AI technologies for
personalized content recommendations, realistic visual effects, and automating video
editing and production.
Microsoft and media companies: Microsoft is working with NBCUniversal Media, Disney,and Warner Bros. Discovery to develop AI tools for news production, content creation,and video game development. Microsoft also offers the Azure OpenAI Service for media
companies to develop their own Gen AI applications.

02 | The Technology Side of Things

20

03

Outlook & Exploring the Debates andChallenges Surrounding Gen AI

03 | Outlook & Exploring the Debates and Challenges Surrounding Gen AI

21

The rapid advancement of GenAI has opened new possibilities for media companies,
offering innovative ways to create and distribute content.
The adoption of Gen AI across various media sectors has been progressing at different
rates, reflecting the unique challenges and opportunities within each industry segment.
In the music sector, AI is making strides in areas such as composition, production, andmarketing, with major players like Spotify, Apple, and Google actively integrating AIdriven solutions. In contrast, the film and television industries have been slower to adopt
AI, as the industry paused to consider the role of AI in the creative processes during
the writers and actors strikes of 2023, and instead primarily focusing on enhancing
content recommendation algorithms and automating certain aspects of production andpost-production including localisation, lip-synching and background effects. Meanwhile,
the publishing sector has seen AI adoption in areas like automated content generation
for marketing and personalised recommendations, but the technology‘s impact on thecreative process remains limited. The advertising industry has embraced AI more rapidly,
leveraging its capabilities for targeted marketing, ad personalization, and performance
analysis. Overall, the rate of Gen AI adoption across media sectors is influenced by
the specific needs, challenges, and opportunities within each industry, as well as thereadiness of stakeholders to embrace and invest in AI-driven solutions.
As Gen AI becomes increasingly integrated into the media landscape, it is essential
for organisations to address the challenges and opportunities that come with thistechnology.
In this discussion, we raise five considerations later on that media companies should
consider as they navigate the complex world of AI integration, touching on topics such as
ethical standards, risk mitigation, compliance with international guidelines, governancepolicies, transparency, and the balance between efficiency and efficacy.

Outlook: Gen AI‘s Impact on Media & Creative Industries
The future of generative AI is incredibly promising, with rapid advancements in bothclosed and open-source domains transforming industries like entertainment, advertising,and content creation. Key developments include:
Remarkable progress in video generation: Techniques like Stable Video Diffusion havemade it possible to generate high-quality videos from single images. This advancement
will revolutionize content creation, advertising, and entertainment industries by reducing
the time and resources required to produce visually stunning videos.
Significant advancements in 3D generation: The ability to infer full 3D scenes fromshort video sequences will have a massive impact on TV, film, and gaming industries. This
technology will enable creators to develop immersive and realistic environments withless effort, leading to more engaging and visually appealing content.

03 | Outlook & Exploring the Debates and Challenges Surrounding Gen AI

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Large-scale multimodal models: With tech giants like Google entering the arena with
their Gemini models, we can expect more sophisticated and powerful AI models that canunderstand and generate content across different modalities, such as text, images, andaudio. This will lead to more seamless and natural interactions between humans and AI
systems, enhancing user experiences in various applications, including virtual assistants,
content recommendation, and personalized marketing.
Open-source mixture-of-expert models: The introduction of models like Mixtral MoE
8x7B signifies that smaller-scale models will become more powerful and accessible. This
will democratize AI technology, allowing more developers and researchers to experimentwith and build upon these models, leading to further advancements in the field andfostering innovation in various industries.
Apple‘s entry with MLX framework: Apple‘s release of the MLX framework
indicates that smaller Language Models (LLMs) will likely run on end-user hardware.
This development will make AI more accessible and integrated into everyday devices,enhancing user experiences and enabling new applications, such as real-time languagetranslation, smart home automation, and personalized content curation.
Emerging regulatory framework: With the European Union’s AI Act, the world‘s firstcomprehensive law to regulate AI is currently inching towards the finish line of thecomplex legislative process.
The final draft text, leaked in January 2024, has led to mixed reactions. While the techcommunity views the regulation foremost as a bureaucratic obstacle for Europe’s AI
ecosystem, the creative- and media industries are generally in favour of the compromise– not least because the bill now encompasses transparency obligations for providers ofgeneral-purpose AI and requires them to comply with applicable copyright law.
Even if the different parts of the AI Act will become applicable (in phases) only from 2025
onwards, companies may already start to familiarize themselves with the new provisions
in good time – both to ensure compliance and to take advantage of the opportunities
arising from the regulation. Furthermore, companies should also keep a close eye on
the various upcoming regulatory developments in other parts of the world, particularly inNorth America, China and India.

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Final thoughts and key questions
Gen AI is already influencing media and creative industries, with AI-assisted software, ad
copy, VFX, book covers, and news articles in the market. However, the full implications
will take time to unfold, as business models and value chains transform gradually, andsocietal factors mediate the impact of technology.
The most significant impact of Gen AI will be in simplifying complex, skilled processes
for a broader audience, particularly in areas where outputs can be immediately verified.
Media companies should focus on applications that empower creatives to produce more,higher-quality work, rather than replacing them with AI-generated content.
AI tools are not yet suitable for wholly replacing human-made content, and media
companies should maintain strong relationships with creators and understand thecreative process and market for media products. Gen AI systems are less suitable fortasks requiring precision, vital system dependencies, or where output appropriateness is
not immediately evident. Traditional software approaches, human input, or a combinationof both will often be the most appropriate solution as we move beyond the stage where
every problem appears to be a nail for our Gen AI hammers.
Any media company looking to harness the power of Gen AI must maintain a focus on
several critical areas:
1) How to operationalise (and balance quality with efficiency)
2) How to ensure quality and how to mitigate reputational and legal risks
3) How to align and comply with global regulations, emerging standards and transparency
4) How to govern AI use
5) How to capture future opportunities and full innovation potential, balancing allof the above.
As the outlook for generative AI continues to evolve, industries must adapt and embracethese technologies while considering the potential regulatory challenges and ethicalimplications. By doing so, they can harness the power of AI to drive innovation, enhanceuser experiences, and create a more connected and immersive world.

03 | Outlook & Exploring the Debates and Challenges Surrounding Gen AI

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generated revenues of €20.2 billion in the 2023 financial year. Bertelsmannstands for creativity and entrepreneurship. This combination promotes firstclass media content and innovative service solutions that inspire customers
around the world. Bertelsmann aspires to achieve climate neutrality by 2030.

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