In its second-quarter 2026 earnings report, Netflix openly stated a number Hollywood usually keeps quiet: it had used generative AI in the production of roughly 300 titles this year. This was no experiment. It declared that AI was beginning to become an ordinary part of the workflow from planning through post-production and distribution.
This article follows the tension that comes before the technology itself. Whenever Netflix creates something with AI, it walks close to red lines around copyright, performers’ rights, and audience emotion. The revealing question is not how much can be done, but where the company decides to stop. The essence of its AI strategy lies in how it draws that line.
What the Figure “About 300 Titles” Tells Us
First, consider the underlying numbers. Quarterly revenue rose 13% year on year to $12.56 billion, with net income of $3.4 billion. Against this sound financial background, Netflix told shareholders it had used AI in about 300 titles. The largest area was post-production—the editing and VFX work after filming that determines the final look.
Co-CEO Ted Sarandos explained that without AI, budget or scheduling constraints would have forced some productions to abandon shots important to the work entirely. Examples included the American Revolution docuseries *The American Experiment*, the Brazilian series *Brasil 70: A Saga do Tri*, and the Indian sports thriller *Glory*. In each, AI directly helped create labor-intensive, costly scenes such as large crowds and battles rather than playing a secondary role in background blur or color correction.
Sarandos repeatedly maintains that AI will not replace creators: great works require great artists, and AI merely gives them better tools. Yet some argue the company is mass-producing cheap content to offset falling engagement, while others worry about the environmental cost of the data centers that run AI. Despite management’s optimism, strong caution persists across the industry.
Legal Teams Draw the Red Lines
At the same time, Netflix is establishing strict rules for production partners. Its internal “Generative AI in Content Production” guidelines draw clear red lines around AI use that can otherwise be left to discretion on set.
Several basic principles stand at their center. Outputs must not reproduce distinctive features of copyrighted works; tools must not retain or reuse inputs or use them to train their own models; generated material must be temporary and absent from final deliverables; and AI must not replace the work of actors or union members without their consent. If the answer to even one condition is “no” or “unknown,” a partner must stop, consult a Netflix representative, and obtain advance approval.
More extensive uses require written approval from legal or another responsible department. Ideation such as mood boards can proceed if it follows the principles, but reports say creating a main character or a setting central to the story with generative AI is strictly forbidden without approval. One exceptional approved case involved using AI in the Korean drama *Squid Game* to create a second killer doll playing Red Light, Green Light with the familiar first doll. Prompts that imitate a specific actor’s traits or name copyrighted works are also excluded.
Netflix is equally wary of imagery that makes real people appear to say things they never said or blurs reality and fiction, even in the background. It presents maintaining viewers’ trust in what they see and hear on screen as an ethical mission.
Affleck’s “Trojan Horse”
Netflix has moved beyond drawing lines and brought technology in-house. In March 2026, it announced plans to acquire InterPositive, the stealth AI startup founded by actor and director Ben Affleck, for as much as $600 million. For a company that preferred internal development and avoided large acquisitions, this was its biggest deal since the roughly $700 million purchase of the Roald Dahl Story Company in 2021 and a clear strategic turning point.
InterPositive’s technology differs fundamentally from ubiquitous general-purpose video generators. It is not a magic box that produces a movie from typed text. Believing existing video models fell short of Hollywood standards, Affleck filmed proprietary data in a controlled studio and used it to develop a model that understands continuity and visual logic. In practice, it trains custom AI on footage creators have already shot and accurately takes over tedious tasks such as removing wires, fine-tuning framing, correcting lighting, and filling missing shots.
The acquisition’s value goes beyond technical ability. Hollywood distrust of generative AI runs deep, and figures such as James Cameron openly describe the prospect of AI replacing actors as frightening. Chief Content Officer Bela Bajaria and CPTO Elizabeth Stone therefore emphasize that the technology is designed to empower creators rather than replace them. Affleck, himself a leading director and actor, states that AI lacks human judgment and accumulated experience and developed the tools with constraints protecting creative intent. That makes a powerful case for Hollywood acceptance. After the acquisition, Affleck became a senior adviser to Netflix, leading adoption and responsible development—a trusted bridgehead within the creative community.
Dubbing May Accelerate, but People Make the Final Reading
AI is also changing localization, which supports global distribution. With most members living outside the United States, lowering language barriers directly supports Netflix’s growth. Translation, casting, studio recording, and mixing once took months; reports say combining speech recognition and machine translation has compressed the process to weeks, increased the number of languages handled in parallel, and may reduce budgets.
For dubbing itself, Netflix is described as using a system called DeepSpeak, which analyzes the original voice and emotional tone and creates synthesized speech in the target language. Technology that synchronizes audio with lip and facial movement is also used alongside solutions from specialist providers such as Deepdub to capture dialects and cultural nuance. Automated transcription and machine translation are used for subtitles as well.
Netflix does not leave these systems fully autonomous. Machines still miss subtleties such as irony, humor, and idioms, so professional linguists and native speakers always review AI drafts. The spread of globally successful Korean titles likewise emphasized conveying the flavor of language rather than translating literally. Translators and dubbing directors are not simply disappearing; their roles are shifting toward editing and selecting among large volumes of drafts.
Permission Does Not Guarantee Emotional Acceptance
This system of boundaries and internal development may appear well controlled, but legal clearance does not guarantee public acceptance. The reality program *Wonka’s The Golden Ticket*, scheduled for September 2026, brought that tension to the surface. Netflix announced that it would synthesize the voice of actor Gene Wilder, who died in 2016, with technology from AI audio company ElevenLabs and use it for narration. Based on the world of the 1971 film *Willy Wonka & the Chocolate Factory*, the program formally obtained permission from his estate. His widow, Karen B. Wilder, also issued a positive statement about bringing his charm to a new generation.
Even so, condemnation erupted on social media. Critics asked whether it was ethical to digitally revive after death the voice of an actor who died without knowing AI existed. Some called it “zombie copyright,” a distorted system allowing corporations to monetize the legacy of the dead without limit. Others argued that iconic performances should remain untouched regardless of permission. An unbridgeable gap remains between the legal and commercial clearance of family consent and fans’ emotional acceptance.
The same gap appeared in Japanese animation. The 2023 experimental short *The Dog & The Boy*, created by Netflix Anime Creators’ Base with WIT Studio and rinna, generated controversy for using image-generation AI for every background. Against the explanation that it addressed labor shortages, the end-credit label “AI (+Human)” angered artists by appearing to reduce human skill to a subordinate addition. Many argued that the real problem was a structure unwilling to pay fair wages rather than a shortage of workers. Japanese animators are said to sometimes work for low pay amid chronic understaffing, and Hayao Miyazaki’s earlier dismissal of AI animation as “an insult to life” was also cited. Director Ryōtarō Makihara said general-purpose AI was used only to a very limited degree and that the main tool was a custom AI trained solely on backgrounds for the project. Again, the technical reality and public reception diverged.
The Winner Will Not Be the Company with the Strongest AI
Netflix’s investment in AI talent reflects its commitment. Generative-AI product-manager listings range from $240,000–$300,000 at the low end to $700,000–$900,000 at the high end. The upper figure combines base pay and stock compensation; Netflix pays no bonus and lets employees choose the salary-to-stock ratio. It was seeking not engineers who make attention-grabbing videos, but leaders who can work across R&D, legal, and privacy and bring AI safely into Hollywood’s stringent environment. Its repeated emphasis on quality, controllability, and compliance aligns neatly with stricter guidelines and the InterPositive acquisition.
Viewed together, these developments suggest that the next entertainment-industry winner will not necessarily have the strongest AI. Success depends on combining AI’s overwhelming productivity with the emotional and ethical complexity experienced by human creators with as little friction as possible. Draw boundaries, manage them through legal teams, and deliver technology from within the creative community: the system Netflix is assembling may become a standard for the next generation of production.
