Case Study: Netflix’s AI-Powered Multilingual Content Localization
This is a paper presented by Dimitrios Telidis, a graduate of the Global Digital Marketing and Localization (GDMLC) program. This paper presents the work being produced by students of The Localization Institute’s programs. The contents of this Paper are presented to create discussion in the global marketing industry on this topic; the contents of this paper are not to be considered an adopted standard of any kind. This does not represent the official position of Brand2Global Conference, The Localization Institute, or the author’s organization.
Today, streaming platforms like Netflix need to make their content easy to understand for people all over the world. Netflix is available in more than 190 countries, so making shows and movies available in many languages is very important to keep viewers interested. In fact, about one out of every three people watching Netflix are watching shows in a language other than English, which shows how important subtitles and dubbing are for reaching a global audience.
To handle the huge amount of content needed and languages, Netflix now uses AI to help with translating, subtitling, and dubbing. These AI tools help speed up the process and make it easier to offer content in more languages, even if the quality is not perfect. This case study looks at how Netflix uses AI for localization, which technologies it uses, who it works with, and some of the problems and controversies that have come up mainly affecting the human ethics of the work.
AI in Netflix’s Localization Workflow
Traditionally, localization relied heavily on human translators and voice actors. However, advancements in AI have introduced tools that can automate aspects of translation and dubbing. Netflix has embraced these technologies to improve efficiency and scalability in its localization processes.
One significant development is the use of AI for dubbing. Netflix has implemented a program called DeepSpeak, which utilizes AI to synthesize voices that match the original actors’ performances, enabling seamless dubbing across different languages. A technology that analyzes lip movements, pitch, and rhythm to create synchronized dubbed audio, enhancing the viewing experience for international audiences.
In addition to dubbing, AI assists in subtitling by automating transcription and translation processes. Tools like VideoLingo aim to generate high-quality subtitles and dubbing, facilitating global content accessibility. These AI-driven solutions help Netflix meet or reach the growing demand for localized content efficiently.
Despite these advancements, the integration of AI in localization has sparked debates. Critics argue that AI may compromise cultural nuances and the authenticity of performances. Furthermore, the use of AI-generated voices raises ethical concerns regarding consent and compensation for original actors. These issues underscore the need for careful implementation and oversight of AI technologies in the entertainment industry.
Netflix’s AI Localization in Action
Netflix employs AI technologies at various stages of its localization workflow to enhance efficiency and maintain quality.
AI-Driven Dubbing: Netflix’s DeepSpeak program represents a significant advancement in AI-driven dubbing. This technology synthesizes voices that closely mimic the original actors, allowing for more natural and synchronized dubbed audio. By analyzing facial movements and speech patterns, DeepSpeak ensures that the dubbed content aligns seamlessly with on-screen performances, improving the viewing experience for non-native audiences.
Automated Subtitling: Netflix applies advanced automatic speech recognition systems to transcribe audio, drastically speeding up subtitle creation. These transcripts are then run through neural machine translation engines for dozens of languages. However, raw AI output is always reviewed and edited by professional linguists and native speakers to avoid errors or awkward phrasing. Netflix’s internal research also explores simplifying English dialogue before machine translation, improving the accuracy of subtitles in other languages.
Audio Description & Accessibility: Another area where Netflix has applied AI is audio description for visually impaired audiences. In 2023, the limited series ‘’All the Light We Cannot See’’ featured some of Netflix’s most detailed audio descriptions to date, generated with the help of an in-house AI. The AI system was able to analyze on-screen elements, like characters, action scenes, and various settings, and automatically draft descriptive narration of each scene. This was then likely reviewed and refined by human writers, but it showcases AI’s ability to scale up accessibility features. Observers noted that the AI-tailored descriptions even adjusted to context, providing richer detail than previous manual efforts. By deploying AI in this way, Netflix can more efficiently produce audio descriptions in multiple languages, making its content more inclusive. It aligns with a broader industry push to use AI for expanding accessibility options, such as sign language avatars, in the future.
Human Quality Control: While AI enhances efficiency, Netflix maintains human oversight to ensure the quality and cultural sensitivity of localized content. Professional linguists and editors review AI-generated subtitles and dubbed audio to preserve the original tone and context. This hybrid approach combines the speed of AI with the nuanced understanding of human experts.
Challenges and Controversies: Using AI for localization has caused some controversy. Many people argue that AI dubbing doesn’t have the same emotional depth or cultural understanding as real voice actors. There are also ethical concerns about using AI to copy someone’s voice, especially if that person is no longer alive or did not give permission. Sometimes, AI technology can even make things worse for viewers. For example, when Netflix released an AI-upscaled version of the show “A Different World,” some people complained about distorted visuals and unnatural effects. While AI makes localization faster, cheaper, and easier to scale, it can also miss the creative details, struggle with humor and idioms, and threaten jobs for translators and voice actors. Because of these issues, unions like SAG-AFTRA are pushing for rules to make sure voice actors are paid fairly and give their consent before their voices are used by AI. Quality is still a challenge, and some viewers say that AI-dubbed shows sound awkward or lack real emotion.
Implications for the Media Industry
Netflix’s use of AI for localization shows how digital content can now reach a global audience faster and more affordably. For marketers, this means they can launch worldwide campaigns and multilingual content simultaneously, boosting global engagement. However, it’s still important to use human editors to ensure jokes, cultural references, and emotional tone resonate in each market.
For localization professionals, AI is not a replacement but a tool that changes their roles. Translators and dubbing directors are becoming editors and quality controllers for AI-generated content, which means new skills are needed. Many vendors now train their staff to work alongside AI, and industry groups stress the need for human oversight and ethical standards.
As AI makes content localization cheaper and faster, more shows can be offered in many languages, including live events. Still, companies like Netflix need to be transparent, respect performers’ rights, and maintain quality to keep audience trust. The best approach is to use AI for speed and scale, while relying on humans for creativity and cultural accuracy, ensuring global content still feels local and authentic.
Overall, I found the course to be extremely interesting. I gained new insights, particularly in the areas of Globalization and SEO, which I had not explored before. The course covers a wide range of topics, and delving deeper into them made the experience even more engaging. With each lecture, the knowledge I gained became increasingly valuable. I am confident that I will recommend this course to my colleagues as well.
References:
2: https://gtelocalize.com/netflix-localization/
3: https://www.meer.com/en/92522-netflixs-deepfake-dubbing-sparks-outrage
4: https://www.aibase.com/news/12120
5: https://www.theverge.com/news/625904/netflix-a-different-world-ai-upscaling-nightmare
7: https://ubos.tech/news/netflixs-ai-upscaling-controversy-a-different-world-in-focus/
8: https://aibusiness.com/verticals/sag-aftra-mandates-consent-pay-for-ai-use-of-actor-voices-in-ads
Disclaimer: Copyright © 2021-2025 The Localization Institute. All rights reserved. This document and translations of it may be copied and furnished to others, and derivative works that comment on or otherwise explain it or assist in its implementation may be prepared, copied, published, and distributed, in whole or in part, without restriction of any kind, provided that the above copyright notice and this section are included on all such copies and derivative works. However, this document itself may not be modified in any way, including by removing the copyright notice or references to The Localization Institute, without the permission of the copyright owners. This document and the information contained herein is provided on an “AS IS” basis and THE LOCALIZATION INSTITUTE DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION HEREIN WILL NOT INFRINGE ANY OWNERSHIP RIGHTS OR ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.
