Netflix is now using generative AI — but it risks leaving viewers and creatives behind

NETFLIX’S recent use of generative artificial intelligence (AI) to create a building collapse scene in the sci-fi show El Eternauta (The Eternaut) marks more than a technological milestone. It reveals a fundamental psychological tension about what makes entertainment authentic.

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The sequence represents the streaming giant’s first official deployment of text-to-video AI in final footage. According to Netflix, it was completed 10 times faster than traditional methods would have allowed.

Yet this efficiency gain illuminates a deeper question rooted in human psychology. When viewers discover their entertainment contains AI, does this revelation of algorithmic authorship trigger the same cognitive dissonance we experience when discovering we've been seduced by misinformation?

The shift from traditional CGI (computer-generated imagery) to generative AI is the most significant change in visual effects (VFX) since computer graphics displaced physical effects.

Traditional physical VFX requires legions of artists meticulously crafting mesh-based models, spending weeks perfecting each element’s geometry, lighting, and animation. Even the use of CGI with green screens demands human artists to construct every digital element from 3D models and program the simulations. They have to manually key-frame each moment, setting points to show how things move or change.

Netflix’s generative AI approach marks a fundamental shift. Instead of building digital scenes piece by piece, artists simply describe what they want and algorithms generate full sequences instantly. This turns a slow, laborious craft into something more like a creative conversation.

But it also raises tough questions. Are we seeing a new stage of technology — or the replacement of human creativity with algorithmic guesswork?

El Eternauta’s building collapse scene demonstrates this transformation starkly. What would once have demanded months of modelling, rigging, and simulation work has been accomplished through text-to-video generation in a fraction of the time.

The economics driving this transformation extend far beyond Netflix’s creative ambitions.