The DPP Leaders’ Briefing 2025 gathered more than 1,000 attendees and key decision-makers from over 30 major media organisations. Credit: DPP

This is the first of a three-part post about a few key insights and findings that I came across when attending the Digital Production Partnership (DPP) Leaders Briefing 2025 in London. The DPP is one of the most important trade associations in the media industry that brings together senior executives from major media organizations. More than 1,000 attendees came to this conference held on November 18 and 19.

Across the two days of the DPP Leaders’ Briefing, you could almost forget who worked where. Once people stopped talking about their logo and started talking about the technical and management problems they were facing, the patterns lined up across major media, news, broadcast, and entertainment organizations.

Key questions that emerged across most presentations:

• How and where do we use AI in production rather than in slideware?
• How can we trust AI tooling and agentic solutions while more decisions are assisted or automated?
• Do we have the right integrations and security mechanisms in place?
• How do we turn deep archives, dailies, and live content into something companies can leverage to reduce costs, increase revenue, and boost quality?
• How do we avoid vendor lock-in while the technology continues to advance at a breakneck pace?
• How does our tech stack need to adapt to accommodate this level of flexibility?
• How do we survive the new content and distribution economics of an AI-driven internet and aggressive hyperscalers?

If you needed a one-line summary of the conference, it is this:

“Despite the high priorities for media companies in AI implementation and automation, the reality is that so far for many players internal business engagement and operational effectiveness have been far more challenging than actual tech delivery”

Another risk discussed during the event was relying on legacy workflows to define the future of work in media.

As an executive from RTL said:

“If you narrow it to KPIs too early you’ll be optimizing what you already have”.

In other words, media enterprises will not be investing in learning what they need to learn and building new workflows from scratch.

Uriah Smith’s 1899 “Horsey Horseless”, a car fitted with a fake horse head, is the ultimate cautionary tale of “optimizing what you already have” rather than trusting a completely new workflow.

To innovate faster, partnerships and collaboration were mentioned as key by C-Level executives. However, organizational challenges remain in the Enterprise space.

For CEOs media tech partnerships are key to be successful. The DPP provided a space to foster those relationships. Credit: Imaginario AI.

If there was one thing CTOs agreed on, it is that technology is now the easy bit, but people and culture are not.

A DPP chart on leadership challenges placed the biggest challenges on organizational dynamics:

• 75% of CTOs said their biggest issue is change management. Not a specific technology, not a security threat, but the basic job of getting people to work in new ways.
• Securing cross-business engagement came next at 50%.
• Technology project delivery only showed up in the middle.
• Recruiting and retaining talent, securing executive buy-in for tech investment, and keeping employees motivated followed behind.
• Improving diversity within the tech function did appear on the list but was rated by just 9% as their single biggest challenge.

The DPP’s CTO Survey 2025. Management and cross-business engagement remains the main barrier for innovation and AI adoption.

During the conference, plenty of commercial media companies, in particular, said that they need suppliers to act as collaborators rather than just traditional providers.

This was confirmed by the DPP CTO survey: the majority chose “collaborative” as their preferred role for vendors, with only a small minority wanting them to stay “supportive.” Such groups, like Public Service Broadcasters (PSBs) and non-profit organizations, leaned more toward “supportive” than “collaborative,” but very few wanted suppliers to be hands-off in an arm’s-length posture.

The DPP’s CEO Survey 2025. Technical partnerships are a top priority for leaders in this space with 85% stating they are being proactive or opportunistic. Credit: DPP.

The CEO survey backed that up with a clean headline: 85% of media tech CEOs say they prioritize partnerships. These ecosystems are evolving from simple integrations to “deep collaborations aimed at solving shared customer challenges.” In plain language, everybody realizes they cannot solve this alone at the current pace of innovation in AI.

However, the mood around AI across the event was at the same time strangely cautious for a technology that dominated the conference agenda. Several people warned about “AI FOMO” quietly driving bad decisions.

One NRK executive even said, without much sugar-coating, “Don’t fall into vendor lock-in, I’m not your bitch.” The line landed partly as a joke, but the sentiment was serious.

Organizations want partners who are honest about what they can really deliver, who will give directional pricing and modular solutions early rather than hiding behind all-encompassing solutions and five-year contracts, and who are willing to integrate with rival systems when that is what the customer needs.

AI adoption playbooks that are working in Enterprise

Groupe TF1, with Olivier Penin as Director of Innovation, remains as one of the examples of successful leadership implementing AI at scale. 75 PoCs last year; 20 use cases industrialized including AI native content studios. Credit: DPP.

Advice given during the conference: Start small, with one video workflow, one team, and one function. Use your own content, style guides, and rights data, so the solution reflects your reality. Pick problems where gains are clearly measurable: time saved, errors reduced, fewer manual touches, faster time to air. Keep humans in charge of outcomes.

None of that is glamorous, but it is where the real progress is happening. With Imaginario AI, this is exactly how we have been driving adoption of our solutions: starting small with a limited pilot in a specific function and landing wider corporate-level MSAs later.

Another golden nugget from the event for international media tech vendors: the DPP’s CTO survey mentioned that commercial media companies based in the US are more optimistic about the future (and therefore willing to invest more and experiment) than public service organizations (most of them based in Europe). However, PSBs expect a budget increase next year.

Where this leaves us

Pulling all of these threads together, you get a picture of an industry leaving its AI demo phase and entering the infrastructure phase.

AI and cloud are no longer bolt-ons. They are becoming part of the media supply chain from ingest and logging through post, archive, versioning, localization, compliance, marketing, scheduling, and consumption.

At the same time, most CTOs freely admitted the industry is only at a “developing” stage of maturity. The next three years are about turning experiments into dependable systems.

… and the organizations that seem to be making real progress shared a few traits during the event:

• They treat AI as operational technology, not as an innovation showpiece. As one speaker said: “AI is not the strategy, it’s a means to an end.”
• They keep humans clearly in charge for decision-making and supervision, with AI in a constrained co-pilot role… at least for now.
• They recognize that rights, data, and AI intelligence (in that order) will unlock true value. They invest in in-video metadata, not just asset-level metadata and cloud infrastructure.
• They take change management, specialist partnerships, and world-class UX design as seriously as they take models and buying GPUs.
• Those adapting faster are getting closer to their core strengths in premium content production (e.g., TF1, RTL) rather than trying to build all AI capabilities themselves.

Partners with all-encompassing, monolithic solutions slow companies down rather than help them get to the next wave of video intelligence and automation.

On the contrary, many companies like Freemantle mentioned that partnering with smaller tech vendors normally provided that level of personalized and high-touch support required by Enterprises. Those specializing in AI, need to be API-first, modular, and that serve core areas such as metadata generation/enrichment, model fine-tuning, and training based on the client’s data and context are the perfect co-pilots in this sprint to innovate.

For those of us building AI-enabling solutions and platforms in this space, the engineering and UX bar is high and goes beyond “we have a clever model.”

We need to help enterprises build their own capabilities on their own terms and focusing on specific use cases. Help them with specific AI razor blades with native integrations and modularity, rather than vendor lock-in with middle-of-the-road solutions.

Other challenges vendors need to understand: clients want automation with control, intelligence with explainability, cloud scale with sovereignty (many times fully on-prem), and AI with genuinely human-centered UX. All with full transparency.

The honest reflection of the industry and the openness to collaborate is what rreally defined the DPP Leaders’ Briefing this year.

Behind all the fear slides and maturity charts, you could feel something else: the sense that the industry has stopped arguing about whether this transformation is happening and has started implementing how to do it without breaking the core strengths that made media companies leaders in the first place (hint: premium content).

To their benefit, content is still king and the time to catch the AI wave is now.


About Imaginario.ai
Backed by Techstars, Comcast, and NVIDIA Inception, Imaginario AI helps media companies turn massive volumes of footage into searchable, discoverable, and editable content. Its Cetus AI engine combines speech, vision, and multimodal semantic understanding to deliver indexing, simplified smart search, automated highlight generation, and intelligent editing tools.

In the constantly-changing landscape of applied AI, the relationship between humans and our new artificial friends is the hot topic, from chats at the water cooler at work, all the way to the White House.

While the fear of AI replacing the “median human”, in words of Sam Altman, is a common concern, the data paints a different picture – one where AI and humans working together can unlock new levels of productivity and innovation. Note: this not only applies to the media and entertainment industry, but other sectors as well.

The untapped potential of human-AI collaboration

According to a study by Accenture, AI has the potential to increase average productivity by up to 40% when used to augment and empower human workers, rather than replace them entirely. This finding is echoed by a Deloitte survey, which revealed that only 16% of organizations are currently using AI primarily to assist workers in developing insights and the majority are still using AI mainly for automation and cost reduction.

This suggests there is massive untapped potential in using AI to enhance human capabilities such as creativity, and this was a huge theme we saw bubbling to the surface at NAB Show 2024.

As Mike Folgner, AI entrepreneur, said during the show:

“Make the effort to understand where it can fit in your workflow. Just embrace the fact that it’s going to be here, and we just need to figure out how it’s going to make our lives easier and better.”

The important point here is to understand the “how and why” of AI to better integrate it into our workflows and get ahead of the curve.

Superminds: the power of machines and people working together

The potential of human-AI collaboration goes beyond just increased productivity. Research by the MIT Center for Collective Intelligence has found that “superminds” – groups of humans and AI working together – can outperform either humans or AI working alone on complex problem-solving tasks.

This synergistic relationship between humans and AI was emphasized by Hao Li of Pinscreen:

“What AI does is that it’s just processing all the data in a way that it’s easier for us to understand what it is, or even synthesize new content in a more efficient way.”

This said, not everything will be wonderful. Any technological revolution brings change, which means some jobs will no longer exist in the future. But new ones will emerge that combine AI technologies with human skills, ingenuity and experience. 

When the automobile was invented, horse-carriage drivers, blacksmiths and others became irrelevant for a large part of society. But this unlocked new roles like truck drivers, taxi drivers, mechanics, factory workers, and more. This is in addition to accelerating the exchange of goods and services globally.

Just like cars in the 20th century AI – properly applied – will let us get where we need to go an order of magnitude faster, with humans staying in the driver’s seat.

The future of human-AI collaboration

It’s difficult to disagree with Renard Jenkins, President of the SMPTE, who predicted:

“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 take a look at everything we have and see where we can actually use it.'”

Alejandro Matamala Ortiz, Co-Founder and CDO of Runway, agreed, saying that “we’re still at the beginning. We have only seen some sneak peeks of the potential of this technology.”

Dado Valentic of Colourlab AI pointed out that – contrary to a lot of the media coverage suggesting AI will lead to mass unemployment – many people who were never even considering becoming creators may find their ways to new careers. AI will make us specialist and multi-disciplinary at the same time as it accelerates our learning curve to learn and apply new skills.

“[Many people] learning color grading have become kind of recreational colorists (…) This means that instead of you having to look for work as a colorist at the post-production facility, you might choose to work for some creator or you might become a creator yourself.”

Microsoft’s Paige Johnson doubled-down on the company’s aim to create a world in which humans own, and are aided by, virtual AI copilots, stating that “The intention has not been to get humans out of the loop but rather to make more impact for every human interaction that happens. Personalization at scale.”.

Naturally, as with any massive technological shift, there is a tendency to worry about the impact on ourselves, and society at large. But we came away from NAB Show 2024 with the impression that the media and production industry is looking at AI with clear eyes and, rather than being worried about the impact, is excited by the possibilities.

As Paul Trillo, LA-based AI Filmmaker and Director at Trillo Films, told a panel audience:

“The more you’re scared of something, the more you should learn about it. The less you learn about something, the more scared you’re going to be.”

Similarly Pinar Seyhan Demirdag of Cuebric encouraged us to “stop being fascinated by computation and technology and start being fascinated by humans that invent.”

There’s a clear goal shared by all the companies we heard from, which we fully agree with: AI and humans working together to unlock unprecedented levels of productivity, problem-solving capabilities, and new opportunities for creativity and innovation.

This movement has many names right now: the cyborg approach, copilots, ai agents, co-intelligence, superminds. Whatever you choose to call it, by understanding the “how and why” of AI, we can position ourselves at the forefront of this transformative technology. The time to experiment and try out these technologies is now. 

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Article credits

Posted by

Jose Puga

Originally published on

May 7, 2024

Filed under

Events

With image generation from

OpenAI

And TikTok creation from

Imaginario AI

In the rapidly evolving world of film production and applied AI, the integration of cutting-edge technologies is not just a trend but a game-changer. This was clearly showcased in the recent release for the faux sci-fi movie, “Cowgirls on the Moon.” Crafted using the latest advancements in cloud computing and using various generative AI tools, the project gives us a glimpse into to the future of filmmaking.

NAB Show 2024 served as the perfect platform for an insightful discussion on this extremely interesting project. Ron Ames, the producer behind Amazon Prime’s series “The Lord of the Rings: The Rings of Power,” and Katrina King, global strategy for content production at AWS, took the stage to share the story of how this project came about.

A rocketship idea

It all started as a joke. “Let’s do something completely out there. Something weird like ‘Cowgirls on the Moon’”, ” Katrina King explained. “We used generative AI in almost every step of the process to really just assist the artists. It was a joke, but nobody came up with a better idea, so that’s what we went with.”

They had almost no budget, a small team and an extremely short timeframe to deliver. The outcome: 54 full shots that involved virtual production, VFX, cloud rendering to power generative AI tools, live action production and compositing. “We wanted to see how hard this was going to be”, added Katrina during a panel discussion at NAB 2024. Check out the panel highlights below.

Out of this world production tools 

The two main tools used were Cuebric and Runway ML. Runway was used to generate 2D concept design and storyboards (e.g. the robotic unicorns), while Cuebric was used to turn those concepts into film-ready backgrounds for green screen and virtual production. These were finally integrated into Unreal Engine, automating various technical aspects of the production and allowing dynamic camera movements, creating a realistic sense of depth applying layer and object segmentation.

Anthropic’s Claude 3 large language model was used to brainstorm various slogans and parts of the script. “None of them were usable straight-up, but provided us with some inspiration for the hairspray”, said King. Baselight was used for color grading skin tones and various other aspects of the project. Finally AWS Deadline was used to bring everything together and render assets.

As this project demonstrates, AWS is actively exploring new applications for generative AI tools that support artists and media companies in their work, making their processes enormously more efficient. As these tools evolve, they continually uncover new use cases that simplify daily tasks, automate mundane technical processes, and free up artists to focus more on creative endeavors.

Collaboration at the speed of light

The discussion also highlighted how cloud and AI tools are opening up collaboration between teams in various locations – Vancouver, London, LA, Boston, Idaho, Switzerland, Turkey, Tucson, and the Netherlands.

“We first said, ‘We want these machines to be Linux.’ But then we changed our minds. ‘Now we want them to be Windows.’ Literally in minutes we had new machines up and running,” Ames explained, to illustrate the agility that cloud computing brings to modern filmmaking.

It’s not just a phase

It’s clear that the intersection of technology and creativity in filmmaking will continue to expand, offering more dynamic, more affordable and immersive ways to tell stories.

The tools we’re seeing pioneered at the professional end of the media industry will trickle down to prosumer and amateur creators quickly, enabling professional-grade filmmaking to be done in a fraction of the normal time and on a shoestring budget. It’s a pretty exciting time to be working in the creative industries.

Check out Cowgirls on the Moon below.

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Article credits

Posted by

Jose Puga

Originally published on

May 2, 2024

Filed under

Events

With audio enhancement from

Adobe Premiere

And image generation from

OpenAI

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.

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Article credits

Posted by

Jose Puga

Originally published on

April 30, 2024

Filed under

Events

With quote extraction from

OpenAI

And TikTok creation from

Imaginario AI