Key Points
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Netflix has used generative AI workflows in roughly 300 titles in 2026, mostly for post-production tasks like crowd enhancement and historical sequences.
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The InterPositive acquisition and proprietary tools give it an edge over studios relying on third-party visual effects houses.
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Smart AI adoption is becoming table stakes; the competitive question is execution, not whether to use the tools.
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Netflix (NASDAQ: NFLX) would like everyone to know that generative AI is transforming content production. The company’s Q2 shareholder letter mentions AI tools being used in roughly 300 titles this year. Co-CEO Ted Sarandos highlighted a documentary called American Experiment that featured 17 minutes of AI-enhanced footage, produced “twice as fast and at half the cost.”
That’s impressive. Also, it’s not exactly new.
The orcs got there first
In 2001, Peter Jackson needed to fill the screen with thousands of soldiers for his ambitious Lord of the Rings battle sequences. Traditional methods would have required either ruinous budgets or a lot of very patient extras. So Jackson’s Wētā Digital company built MASSIVE, a software package that generated autonomous digital agents capable of fighting, fleeing, and dying on their own. It was AI-powered production before AI was cool.
The pitch back then sounds familiar: Once-impossible shots are now achievable. Productions no longer have to “leave out key sequences” due to budget constraints. It’s the digital automation of studio grunt work.
MASSIVE went on to populate zombie hordes in The Walking Dead, stadium crowds in countless sports movies, and anything else featuring “epic scale.” The software was genuinely transformative. It also didn’t change who directed movies or how stories got told.
Netflix’s current AI toolkit includes InterPositive (acquired in Q1 2026), something called iLine, and an “animation lab.” The cited use cases are crowd enhancement, historical battle sequences, and “world-building establishing shots.” In other words, the same labor-intensive, repetitive visual tasks that have been candidates for automation since computers learned to render polygons. They’re still using Nvidia and AMD chips, just from their AI accelerator product lines instead of GeForce and Radeon graphics cards this time.
The Photoshop test
Here’s a thought experiment: Imagine a graphic design firm in the 2010s that refused to use Adobe Photoshop or Illustrator, preferring hand-drawing and other “traditional methods.” That firm would not exist for long. The same is true for AI-averse creative endeavors in 2026.
Production technology evolves. Studios that adopt it effectively gain advantages. Studios that don’t fall behind. This has been true since the introduction of sound, color, CGI, and digital editing.
Orson Welles broke the rules with Citizen Kane’s deep-focus lenses in 1941. So did Stanley Kubrick’s 2001: A Space Odyssey, which used rotating centrifuges in 1968. Generative AI is just the next iteration of production tools, not a departure from the pattern.
The relevant question for Netflix investors isn’t whether AI is changing filmmaking. The answer to that is obviously yes, and also obviously no, depending on how you define “filmmaking.” The relevant question is: Can Netflix execute on production technology better than its competitors?
The scale advantage
Netflix has some structural tailwinds here. The company spends roughly $20 billion annually on content, produces in more than 50 countries, and can mandate tool adoption across its productions. Traditional studios work through fragmented pipelines, third-party VFX houses, and more complex labor agreements. Netflix has a production budget comparable to that of a small European country.
Sarandos noted that the InterPositive buyout made sense specifically because it “was created specifically for filmmakers and specifically for filmmaking.” This distinguishes it from general-purpose AI video generators, which tend to produce content that is obviously synthetic. It’s not easy to spoof human creativity when you’re just a bunch of chips and software.
Netflix also has the data to train its own AI models. When you’re producing hundreds of titles per year across every genre and geography, you accumulate a lot of training material.
What the numbers don’t show
Netflix hasn’t disclosed aggregate cost savings from AI. The “twice as fast, half the cost” claim applies to 17 minutes of one documentary. Content amortization is still expected to grow 10% this year. Free cash flow guidance is unchanged at $12.5 billion.
In other words, AI efficiencies aren’t yet showing up in Netflix’s financial model in a material way. The tools are enabling marginal improvements and previously impossible shots, not restructuring production economics. Not yet, anyway.
The talent dance
Sarandos has repeated the same thought on two consecutive earnings calls: It takes a great artist to make great art, and AI won’t change that. Movies are being made by people who make movies.
This is both a genuine philosophical position and a careful labor-relations message. The 2023 strikes are recent memory. Guild relationships matter. Netflix needs to frame AI as augmentation, not replacement, regardless of the long-term trajectory.
The bottom line
Netflix is investing in production technology that competitors will eventually need to match. The company’s scale and centralized infrastructure provide execution advantages. The technology itself is evolutionary, not revolutionary.
Twenty-five years ago, MASSIVE let Peter Jackson put 10,000 orcs on screen. Later, competitors like Unreal Engine and Unity Software offered similar functions. Generative AI lets Netflix enhance crowd scenes and historical sequences at a lower cost. The tools are different. The playbook is the same.
Not using these tools well in 2026 would be malpractice. Using them well is just competent operations, setting Netflix up for continued success.
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Anders Bylund has positions in Netflix and Nvidia. The Motley Fool has positions in and recommends Adobe, Advanced Micro Devices, Netflix, Nvidia, and Unity Software. The Motley Fool recommends the following options: long January 2028 $330 calls on Adobe and short January 2028 $340 calls on Adobe. The Motley Fool has a disclosure policy.
