Not long ago, the thought of AI making a splash in the creative industries seemed completely out of place. Yet here we are, with AI not just making waves, but already transforming how content is created, personalized, and delivered.
Projections point to a $2.5 trillion AI market by 2032 (from $621.19 billion this year). Media and production companies need to pay attention and quickly adopt those use cases that unlock immediate value. But, just as importantly, they need to avoid becoming victims of AI hype.
The real deal on AI in media
With any technological boom comes the inevitable buzz – and AI is no exception. While some are touting generative AI as the next big thing in every conceivable domain, it’s crucial to distinguish between novelties, clickbait and genuinely transformative applications and new workflows emerging. This was one of the core themes of NAB Show 2024, and we saw some amazing examples of genuinely useful AI workflows. This quote from a panel discussion captures this sentiment well:
“There’s so much frenzy around looking for good, solid solutions… it’s going to absolutely transform the industry over the next 10 years, but we’re still not sure how that’s going to manifest yet.”
Marty Roberts, SVP, Product Strategy & Marketing, Brightcove
Renard Jenkins, President of the Society of Motion Picture and Television Engineers (and former Warner Bros exec), pointed out:
“I don’t actually think that we’ve hit the peak of the hype yet as there’s something coming out almost every day and some of these tools have legs. Whether or not they have legs to be standalone tools, or whether they can actually be integrated into a larger pipeline or a larger application altogether, there’s a lot of research that’s going on. If I had to predict, I’d say we’ve got about another 6 to 9 months before we get to that point where everyone says, okay, now let’s slow down and let’s take a look at everything we have and let’s see where we can actually use it.”
Another vein of AI skepticism was voiced by Paul Trillo from Trillo Films Inc., who stressed the importance of involving creative professionals in the development of AI tools:
“The mistake of not including active creative professionals in the development stage of your product. It ends up being isolated, with engineers and researchers working in a black box without knowing who they’re creating for (…) There are decades of animation, VFX, and editing tools and we already speak that language. Some AI companies are not referencing any of that, and it feels like toys a lot of the time. These companies worked to create a functional interface, and you don’t have to copy it, but you can reference that creative language that we’re already used to communicate”.
Paul Trillo, Trillo Films Inc.
The AI surprise in the creative industries
Given that most of column inches involving the creative industries and artificial intelligence are given over to the theft of intellectual property and jobs risks, it may come as a surprise to many that AI is now a pivotal player in the arts and creative sectors.
As well as time-savers such as as logging, searching for scenes, re-editing content for social media, audio sync and more, AI applications are blossoming in areas traditionally dominated by raw human creativity. Editing, filming, and script writing have all been impacted by AI tools, often using generative systems as creative sidekicks rather than straight replacements for people.
Pinar Seyhan Demirdag of Cuebric highlighted during NAB the overlooked utility of AI in creative workflows:
“By focusing on generative AI, we’re missing a lot of utilitarian AI. For example, our tool, Cuebric, is created to streamline the production of 2.5D environments for virtual production and ideation. There is no human in the world that can look at a flat image and tell you the exact meter distance between a house and a mountain, but AI can do that. Our tool does just that.”
In other words, her company is a clear example of a company adding concrete value to the industry by making virtual production cheaper, more personalized, iterative, and accessible. That’s not just hype.
Beyond the obvious applications of Large Language Models (LLMs) and Image Generators in pre-production to generate draft scripts, design ideas, storyboarding, and more, some other concrete and valuable applications of AI in media workflows today include:
- Synthetic dubbing and captioning into dozens of languages
- Transcription-based video editing replacing or complementing timeline-based editing
- Searching for scenes inside videos across vision, speech and sounds (e.g. Imaginario AI specializes on this)
- Audio clean-up, upscaling, generation and track splitting
- Automatic rotoscoping
- Enhancing VFX and animation workflows
- Automatic colour grading
- Generating synthetic music from text prompts
- Generating or extending b-roll content and shots from text-prompts
- Depth mapping from 2D images for virtual production
AI and multimodal data: A match made in heaven
The fusion of AI with rich multimodal data from media and entertainment players is nothing short of transformative. This powerful combo is redefining how media companies (and the AI companies that support them) interact with audiences and exploit their content libraries in a more efficient way.
For small production companies and independent creators, AI is helping filmmakers and creative entrepreneurs iterate faster in pre-production and being able to produce, add visual effects and edit Hollywood-grade content on a shoestring budget, and at lightning speed. In other words, in the near future millions of amateur creators will become one-person content studios and agile content marketing agencies; small production companies will become Hollywood Studios.
Sean King of Veritone explains the efficiency brought by AI tools:
“With newly released tools like OpenAI SORA, content creators will be able to produce short videos rapidly and more cost-effectively, which is especially relevant for ad, marketing and social media campaigns and will lead to new forms of content engagement and monetization.”
Accelerant AI: some core use cases
In addition to major investments in OpenAI, Mistral and other R&D heavy AI startups, Microsoft is also at the forefront of exploring how AI can enhance media production and content management.
Paige Johnson, VP Worldwide Media Industry Marketing at Microsoft, illustrates and expands on this same compelling use of AI in understanding and manipulating media content, similar to the work we’re doing to understand the sentiment and emotions:
“AI can start to read sentiments like funny or read the intensity. If you think about creating a promo clip, and you have an AI find the scenes that are really funny and I want it to include animals, it will either automate the ability for you to look at the potential clips for that, or automate putting together a 90-, 60-, 30-second promo that you can then edit from, saving time and money on those types of tasks.”
Alejandro Matamala Ortiz, Cofounder of Runway ML, encapsulates the journey of exploration the media industry is experiencing with AI:
“I think we’re still at the beginning. We have only seen some sneak peeks of the potential of this technology. We all have seen here many amazing demos and capabilities from research labs and big companies. However, we are still defining how that potential will turn out to be useful applications.”
In other words, the journey towards fully realizing AI’s potential in media and the booming creator economy is ongoing. However, it promises to be as thrilling as it is transformative.
Stay tuned to discover some real-life use cases for AI tools that we saw at NAB Show 2024, in our next video diary coming later this week. Subscribe to our YouTube channel to get alerted the second we publish new videos.
