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In 1984, Ridley Scott was hired to direct a 60-second Super Bowl spot, launching a new tech company. 

Tapped for his cinematic eye and signature world-building, he was expected to deliver something epic, an ad that echoed Orwell’s 1984 and rivalled the visual ambition of Alien or Blade Runner. But when the budget was slashed, he got scrappy. Scott rounded up a few skinheads, doused them in flour, and used mirrors to create the illusion of a massive, dystopian crowd. The spot worked. And that gritty workaround helped introduce one of the most iconic brands of our time: Apple.

As animators, we’ve always adapted to new tools.

What made that commercial memorable had nothing to do with the mirrors or flour. It worked because of the clarity and imagination behind it - Scott’s ability to shape limited resources into something visually unforgettable.

Today, that same conversation surrounds AI.

As animators, we’ve always adapted to new tools. Rotoscoping, performance capture, digital painting... each innovation has reshaped the way we work. AI has already entered our pipelines and is shaping how we build, composite, refine, and stylise. It’s part of the process now. The focus has shifted to how it’s being used, and who is making the decisions.

AI requires human vision to create meaning

Every animated project starts with an idea. Tools help bring that idea to life, but they don’t provide direction or define the story. At LOBO, we’ve been incorporating AI tools for a while, most recently to generate delicate paper textures for Snowball, a film exploring mental health and wintertime isolation. The look needed to feel fragile and ephemeral — something grounded in the emotional tone of the story. Traditional methods couldn’t deliver that quality within the project’s constraints. AI gave us access to a visual vocabulary that enhanced our intent.

What mattered was the creative process behind the film, how we approached tone, emotion, and pacing. AI assisted with executing a specific element, but every decision came from our team.

Apple – 1984

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Above: Ridley Scott's 'scrappy' 1984 Apple spot.


AI tools don’t make the work easier — they shift where the work happens

On some recent projects, AI tools have helped us realise creative ideas that might otherwise have been too labour-intensive or time-prohibitive. But using them didn’t make the process effortless. It simply redirected our attention. We had to design prompts, interpret results, test options, and refine until the images aligned with the tone and purpose of the project. 

The judgement and authorship required by our team remained the same; they just took a new path.

AI doesn’t eliminate the need for animators

There’s growing concern that AI allows anyone to generate content that looks like animation. But craft can’t be simulated. Animation requires an understanding of rhythm, movement, emotional pacing, and visual storytelling - skills cultivated over time and through practice. These aren’t qualities that emerge from a tool. They come from people who know how to shape and structure images into a narrative experience.

AI simply offers a new method for realising the same creative vision.

Generative tools may accelerate parts of the pipeline, but they don’t replace the thinking, intuition, and vision that define animation as a creative form.

We saw the fear play out in real time

While in jury rooms this year, I’ve seen conversations increasingly shift away from a film’s emotional core and visual originality towards debates over what even qualifies as “animation” when AI is involved. Judges questioned whether AI-generated textures, in-betweening, or design elements diminish the artistry or craftsmanship of the work. For some, even limited AI assistance was enough to disqualify a piece.

That reaction reveals a deeper discomfort. For decades, animators have scanned and photographed textures, repurposed stock assets, and used digital manipulation to achieve their visual goals. 

AI simply offers a new method for realising the same creative vision. The process itself isn’t new. The anxiety around the tool is.

SAFE Project – The Snowball

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Above: The Snowball from LOBO, which combined traditional animation with AI.


We don’t need new categories - we need better criteria

Some have suggested that AI-assisted work should be separated into its own award categories or evaluated under different standards. But in practice, drawing lines around tool usage is becoming increasingly difficult. Most 2D films now incorporate 3D workflows, and many stop-motion projects rely on digital compositing. The boundaries have been fluid for a long time.

Trying to isolate AI use in an evolving production environment doesn’t help clarify authorship; it only adds confusion. A better approach is to evaluate the work itself: its clarity, emotional impact, originality, and execution. If the piece reflects strong creative intent and holds together as a work of storytelling, the tools used to make it are secondary.

[Animators have] spent careers adapting to changing tools without compromising creative standards.

Our standards should evolve with our tools. What matters is whether they’re being applied in ways that deepen the work and serve the artistic vision.

We’re in a position to shape what comes next

Animators are uniquely equipped to lead this moment. We understand how visual language works. We’ve always balanced experimentation with precision. And we’ve spent our careers adapting to changing tools without compromising our creative standards.

Every major shift in animation - whether technical or conceptual - has sparked debate and discomfort. AI is simply the next phase in that long lineage. 

The difference this time is that we have a chance to help define how it’s used and what boundaries should exist around it.

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