Anyone discussing Artificial Intelligence in film production today is navigating between two extremes. On one side are the enthusiasts who believe that soon everyone with a laptop can produce Hollywood-quality films. On the other side are the sceptics who dismiss AI-generated content as "AI slop" and see it as the demise of creative professions. The truth, as often, lies somewhere in between. And it is far more exciting than either extreme suggests.
Because Artificial Intelligence is not changing film and video production overnight, but layer by layer. From the initial idea to the storyboard and through to finished post-production, AI-supported workflows are creeping into almost every production step. For studios, agencies, and motion design teams, this means a fundamental shift: not away from humans, but towards a new form of collaboration between creative minds and intelligent tools.
From storyboard to screen: Where AI is already commonplace in film production
The most exciting development is not happening where it gets the most attention. While public debate primarily revolves around fully AI-generated videos – from Sora to Runway to Google's Veo – the real change is happening much more quietly, in the intermediate steps of production.
In pre-production, for example, AI has already initiated a remarkable paradigm shift. Storyboards, which previously required days of drawing, are now created in minutes. Directors and creative directors can thus test much faster whether a scene conveys the desired mood and dynamism. AI-supported mood boards and visualisations are appearing more and more frequently in pitches because they make ideas tangible before a single camera is even turned on. Hannah Elsakr, Vice President GenAI New Ventures at Adobe, aptly describes this change as a shift in mindset from "fix it in post" to "fix it in pre" (McKinsey, 2025).
This shift has enormous consequences for the quality and efficiency of brand film productions. If creative decisions are made and visually validated earlier in the process, the risk of costly corrections in post-production decreases. Dramatic turning points can be A/B tested in the concept phase, scripts analytically broken down, and shooting schedules optimised to use shooting days and resources more efficiently.
In post-production, AI has long been commonplace. Automatic dubbing and localisation, intelligent clipping of large footage libraries, and AI-supported colour correction are standard repertoire for modern studios. The Oscar-winning film "Everything Everywhere All At Once", for example, used AI tools from Runway to implement complex visual effects faster and more cost-effectively – a signal that has sent ripples from Hollywood to regional video production.
The McKinsey forecast: Ten billion dollars and structural change
To understand where things are headed, one should look at the current McKinsey study "What AI could mean for film and TV production" . The analysis surveyed over twenty industry leaders, including studio and production executives, AI innovators, and academics. The result is a nuanced picture that goes far beyond the usual hype.
The study predicts that by 2030, around ten billion dollars in production spending could flow into AI-supported workflows in the US alone. The surveyed industry experts currently see productivity gains in the single-digit percentage range – especially in development, pre-production, and post-production. This initially sounds modest but is a harbinger of profound structural changes.
Particularly insightful is the historical comparison drawn by the authors. Earlier technological leaps, such as digital cameras or CGI, made production more efficient, but the economic added value largely went to the big distributors. A similar pattern is now emerging: the democratisation of production through AI does not automatically mean that creative teams earn more – it initially means that more content can be created with fewer resources. For professional motion design studios , this means defining their added value even more clearly through quality, strategy, and creative excellence.
Sound, voice, sound design: The invisible revolution
In addition to visual possibilities, AI is also fundamentally changing the acoustic side of film production. Modern systems can reproduce voices almost deceptively realistically and automatically translate dialogues into other languages – not with the robotic monotony of earlier synchronisation software, but with intonation, emotion, and natural speech rhythm. For international companies that want to publish their brand films or explainer videos in multiple languages, this is a massive relief.
In sound design, algorithms create realistic soundscapes, fill background atmospheres, and compose music that dynamically adapts to the editing rhythm of a scene. What used to occupy a composer and a sound engineer for days is now created in hours. However, here too: AI provides raw material and suggestions, but the final selection, tuning, and emotional fine-tuning remain a creative decision that requires experience and intuition.
AI also plays an increasingly central role in virtual production – the LED walls that display computer-generated landscapes in real-time and became famous through "The Mandalorian". While such setups are currently still reserved for large productions, creative teams are already using AI image generators on a smaller scale to use concept images as digital matte paintings in the background. For commercials and corporate videos, this means: practically any conceivable setting can be depicted without being tied to real filming locations.
Why "AI-generated" is not a seal of quality – and authenticity wins
This becomes particularly interesting for anyone working in corporate film, brand film, or brand communication. Because while AI tools open up impressive technical possibilities, research simultaneously shows a clear counter-movement on the recipient side.
A study by Belanche et al., published in the renowned International Journal of Information Management, investigated how consumers react to AI-generated images compared to real footage (Belanche, D., Ibáñez-Sánchez, S., Jordán, P. & Matas, S., 2025: "Customer reactions to generative AI vs. real images in high-involvement and hedonic services", International Journal of Information Management, 85, 102954). The results are clear: consumers prefer real images over AI-generated content. The effect is particularly strong for emotional services and decisions to which customers attach high personal importance.
The qualitative analysis of the study reveals the reasons behind this rejection. Companies that use AI-generated images are perceived as impersonal, less professional, and less credible. Particularly sensitive: some study participants felt that the use of AI images was potentially misleading and attributed dishonest motives to the company.
For film production, this sends a clear message: AI can and should accelerate processes behind the scenes and expand creative possibilities. But the visible end result – the film, the animation, the branding video – must still bear a human touch. There is a subtle but crucial difference between a film produced with the help of AI and a film produced by AI. The former is a promise of quality, the latter increasingly a stigma.
AI and illustration: Between creative sparring and stylistic arbitrariness
Especially in animation and illustration, the tension is most evident. Generative AI tools can create concept images, style drafts, and visual references in seconds. For illustrators and motion designers, this is an enormous gain in the idea phase – provided it is understood as a sparring partner and not a replacement.
The danger lies in stylistic arbitrariness. AI-generated illustrations often have a recognisable aesthetic: slightly dreamlike, overly smoothed, with a certain generic perfection that quickly wears off. For professional explainer videos and brand films, where a consistent visual style is essential, this is not enough. An explainer video that is supposed to convey a company's corporate identity needs a design attitude that cannot be derived from a prompt, but arises from a deep understanding of the brand, target audience, and communication goals.
Kevin Lingley, Executive Vice President of AI at Fremantle, puts it succinctly in the McKinsey study: "Creative integrity is so important. It doesn't matter what is used to produce content; viewers need to feel they are being engaged and entertained in the best way possible, and not being lied to" (McKinsey, 2025). Creative integrity is not a nice extra – it is the basic prerequisite for a film to have its effect.
What this means for companies investing in video content now
Companies investing in video contentin 2025 and 2026 face an interesting strategic decision. The temptation to view AI-generated content as a cheap alternative to professional production is great. But case studies from the recent past show that this path carries significant risks.
Coca-Cola's 2025 Christmas commercial, entirely AI-generated, sparked a storm of indignation. McDonald's had to take its AI-generated Dutch Christmas commercial offline after only three days and publicly spoke of an "important learning experience in dealing with AI". The audience is developing an increasingly fine sense for AI-generated content – and the emotional reaction to it is increasingly negative, especially when authenticity is suggested but not present.
The smarter strategy is to use AI as a catalyst within a professional production process. Specifically, this means: AI-supported research and concept development to arrive at better ideas faster. AI-assisted pre-production to create storyboards, animatics, and visual prototypes more efficiently. AI-optimised post-production to accelerate routine tasks such as subtitling, colour correction, and localisation. And at the same time: human creativity, craftsmanship, and strategic thinking wherever emotional impact, brand fit, and narrative quality are important.
Especially for complex technology topics, where it is crucial to make abstract concepts visually tangible, this combination is particularly effective. An AI tool can generate visualisation suggestions, but the didactic preparation and visual translation for a specific target audience still require experienced designers.
The future belongs to the hybrid workflow
The discussion about AI in film production suffers from a false dichotomy: human or machine. The reality in studios and agencies that use this technology most productively looks different. It's about hybrid workflows, where AI takes over repetitive, time-consuming, and technically demanding tasks, while humans do what they do best – tell stories that move.
As the Medientage blog aptly summarises: AI is fundamentally rewiring film, TV, and production. Jobs, value creation, and rights issues will have to be fundamentally renegotiated in the coming years. For creatives and producers who engage with these tools early, a clear competitive advantage emerges – not because they replace humans, but because they elevate human creativity to a new level.
Because in the end, the same applies to film production as to any other form of communication: it's not who uses the latest technology that wins, but who tells the best story. AI only makes it possible to tell that story faster, more efficiently, and more visually impressively than ever before – provided an experienced creative team is at the helm.
You can find an overview of all current developments in our article on explainer video trends 2026.
Would you like to integrate AI meaningfully into your film and video projects? At Brussobaum Motion Design Studio , we combine AI-supported workflows with professional motion design, precise brand management, and clear visual structure. The result is content that doesn't look "AI-generated", but appears strong, creative, and high-quality. Get in touch – we make complex topics understandable, visually strong, and modernly experienceable.
