AI in game localization: Efficiency tool or business risk?

27 min

April 30, 2026

Author: Vojtěch Schubert, Siddharth Sharma

This piece is a heavily updated and expanded version of the article originally published in the Czech gaming magazine LEVEL.

AI is changing how games are made. From procedural generation to NPC dialogue, developers are increasingly relying on machine intelligence to ship faster. So, it’s no surprise that localization has also entered the AI conversation, being on the forefront of this shift. 

But video games aren’t just translated. They’re experienced by real players with diverse cultural and linguistic nuances. And no two games are approached the same way. So, if you care about how your game is experienced globally (not just understood), can AI actually deliver?

First, let’s clear up the terminology

A lot of confusion stems from treating “AI,” “Machine Translation (MT),” and “LLMs” as interchangeable. However, they are far from being the same. 

Here’s how MT and AI LLMs differ:

  • Machine Translation (MT) has existed since the 1950s, with the modern neural MT era beginning around 2010, all with the main purpose to translate. Tools like Google Translate and DeepL are MT engines. 

💡How does MT work?
MT translates one language to another by analyzing patterns in enormous bilingual datasets and generating the statistically most probable translation. Not the most appropriate, not the most creative, not the most contextually aware, but the most probable one. 

  • On the other hand, Large Language Models (LLMs) – what most people mean when they say “AI” today – are a different technology. ChatGPT, Claude, Gemini, and similar LLMs were not designed as translation engines. Rather, translation is one of many tasks they can attempt.

💡How do AI tools and LLMs translate?
AI tools translate by predicting the most likely word based on vast internet-scraped training data and other sources, which brings its own complications including unresolved copyright concerns, biases, and a tendency to “hallucinate” that is factually or linguistically wrong. While AI evolves rapidly, it remains a probabilistic system that can still prioritize linguistic fluency over factual precision.

When it comes to quality, human translation done by experienced linguists remains the gold standard. But when discussing MT vs AI, for certain contexts, language pairs, text types, and levels of creativity or text fragmentation, you may still get better results with “plain” MT than with AI tools. The final outcome, however, depends on various factors (e.g. quality and expertise of project preparation and management among others).

So, any solution must be thoroughly tested before using it in live projects.

The problem isn’t that AI translation is outright bad – it’s that it’s convincingly wrong

Modern AI outputs often read just right. They sound natural and feel literally correct. But beneath the surface, meanings keep shifting.

This is because when an MT engine or LLM processes your game’s dialogue, item descriptions, UI strings, or lore entries – it’s not understanding your game world. It’s not considering your character’s personality, the register of your narrator, or the comic timing of a punchline. 

It’s generating the most statistically average rendering of each string, mostly without the full context.

This is, of course, something a human translator can offer the client: a guarantee that the text is free of hallucinations and inconsistencies. After all, the most serious errors in machine and AI translation are not those where a sentence is obviously wrong. The most problematic ones are those where the sentence sounds perfectly natural but says something completely different from the original.

As Matouš Hájek, chairman of the Association of Czech Translation Agencies, observes:

AI-generated texts are usually appealing at first glance, but they desperately lack creativity and individual style. Frequent, unpredictable, and hard-to-detect hallucinations are also a major issue. When AI is involved in translation, the risk of both minor inaccuracies and fundamental errors increases significantly – often in places where a human wouldn’t expect them, making them more likely to escape notice even during a careful review.

What are the advantages of using AI for game localization?

To be fair, AI does bring some advantages to the table, especially for game developers with limited budgets.

  • Speed is the most obvious one. What would take a human team weeks can be processed in minutes. 

  • Then there’s cost. AI translation is cheaper than hiring experienced translators, especially when dealing with large volumes of text.

  • While human workflows can scale too, AI scales across multiple languages faster and is available at any time, seemingly without scheduling, coordination, or overhead (until you inevitably dig deeper).

These benefits are real, and in certain contexts, they make sense. For example, if you are using AI translation for internal use, prototyping, support tickets, or simply for understanding content across languages, AI performs well. It can act as a fast, accessible layer of comprehension.

But that’s where the strengths begin to plateau.

Especially when you focus on quality. Because while AI is optimized for speed and volume, game localization is defined by precision, context, and intended effect on your audience which may escape the surface of the words.

And this is where the trade-off becomes clear.

Why context is king in game localization

Game text usually doesn’t arrive in neat, self-contained paragraphs. It’s built from thousands of fragmented strings:

  • UI labels

  • Item descriptions

  • Branching dialogue

  • System messages

  • Narrative lines that only make sense in sequence

Players, in particular, are sensitive to these distinctions in ways that general audiences often aren’t. They have paid for your game. They have invested hours in your world. They notice when dialogue feels machine-produced – when a villain sounds flat, when a joke lands with a thud, when inconsistent terminology or style breaks the immersion, or when a cultural reference falls out of thin air.

However, an MT engine processes each string in isolation, with no knowledge of what came before it, what will follow, or what the string is actually doing in the context of the game. 

It doesn’t know:

  • Who is speaking

  • Who is being spoken to

  • What just happened in the scene

  • If a line is serious, sarcastic, or comedic

  • Whether a word is a verb, a noun, or part of a joke

  • That an information from a contextual screenshot changes the obvious translation to a more creative one

So it does what it’s designed to do: it predicts the most probable translation, but not the most appropriate one.

An LLM can be given more context in a prompt, but the context it needs to do game localization well is the entire game, and you need a dedicated human to feed it that. But even with full context, the AI may hallucinate, generating sentences that sound perfect on paper but mean something different. On the other hand, key parts of information may be missing or warped.

Then there’s the technical side.

Many game strings include variables that change at runtime, such as player names, item counts, or dynamic values. The correct handling of a variable (and repositioning it within a translation to comply with various grammar rules for each language) often requires knowing not just what the surrounding sentence means, but what the variable will contain at runtime – information that lives in the game’s code, not in the text string. Only a human, in dialogue with the developer, can reliably get this right.

Real-life examples of AI translation (and what real users think)

A quick Google search brings up tons of real-world examples showing what happens when localization is treated as a pure automated task. Let’s look at some of them.

1. The Alters Backlash

In 2025, The Alters by 11 bit studios (the same team behind This War of Mine) launched to positive reviews. But within days of release, the game found itself at the center of a global controversy after players discovered the undisclosed use of generative AI in the game’s background flavor texts, translations, and image assets.

The first sign came from a Bluesky user who shared a screenshot of the background text from the Captain’s Logs. The text clearly read, “Sure, here’s a revised version focusing purely on scientific and astronomical data” (identical to how AI responds to a rewrite request).

 Source: BlueSky

Soon, multiple players began reporting localization issues in the Brazilian Portuguese version, including incorrect grammar, inaccurate word choices, and AI response texts left inside the game in place of subtitles.

Source: BlueSky

After the allegations began to make headlines, 11 bit studios issued a statement confirming that it in fact used AI during development. The reason given was time constraints. The studio also admitted it had not disclosed any of this earlier – something Steam has required developers to do since January 2024.

Source: Steam

One Steam user’s response was blunt: “Generative AI use is not acceptable. Undisclosed generative AI use is even less so. I would not have purchased with this information, and I will not be buying from 11 bit again.”

Why this matters for game developers

On the surface, the backlash may seem like it was caused simply by translation errors. But as you go through more player responses, it becomes evident that it’s really about how players perceive the use of AI.

Across discussions, one thing was clear: many players don’t see AI-driven localization as neutral. Even when the output is decent, the moment they recognize it’s AI changes how they feel about the game.

2. The Tabletop Simulator incident

In 2021, Berserk Games developers decided to use Google Translate for all 29 languages supported by Steam in their popular game, Tabletop Simulator. They used machine translation, expecting their loyal community would provide free fixes to the machine’s mistakes.

Their Steam product page displayed, “We are excited to see what native speakers in the community can come up with for the most authentic multilingual gameplay experience.”

But what followed was a flood of players criticizing the move on Twitter as they noticed inaccurate translations across languages. While some reported “pan” (camera pan) translating into “frying pan” in German, players from Russia reported words like “Auto Scale” translated to “Vehicle Weighing Scales”.

This illustrates a fundamental misunderstanding: translation is not a mechanical word-for-word swap. It’s a nuanced process that accounts for context, word register, style, and target audience. A true translation bypasses the surface layer of words, going deeper to extract the core meaning, rephrasing it with a precision. Without considering the intended use of the text, you aren’t localizing a game – you’re just breaking it in 29 different languages.

Source: X

Why this matters for game developers

The backlash wasn’t simply over bad translations but rather what this decision signaled – with many believing the developers chose speed over respect for their non-English speaking audience.

Multiple users also criticized the brand for using players as free laborers instead of paying actual professionals, insisting on the importance of hiring human translators who understand the game and its players.

Also read: How important is Steam page localization for your game?

The more critical lesson here isn’t about Tabletop Simulator specifically. It’s about expectations. When you announce localization, players assume it was done properly, and in high quality – as was the rest of your game. The gap between that assumption and AI-generated output is where the trust breaks.

3. Crunchyroll AI subtitles backlash

In October 2023, the premiere episode of The Yuzuki Family’s Four Sons went live on Crunchyroll – and within hours, X (formerly Twitter) user @LossThief flagged something deeply wrong with the subtitles. 

  • 90% of the sentences had no punctuation

  • Possessives were mixed up throughout

  • Lines described the opposite of what was visually happening on screen

Source: X

In one scene, a visibly cheerful character clearly asked the protagonist if he was upset. The subtitle read: 

“What’s the matter? I’m in a bad mood early in the morning.”

The character was happy. The translated subtitle said she wasn’t, reversing an entire moment meant to establish character.

Over 200 comments appeared on the episode page, claiming the subs felt machine-generated and filled with mistakes. The thread went viral. As a result, Crunchyroll had to confirm it would issue updated subtitles.

The incident blew over, but somewhere the suspicion remained. Two years later, in April 2025, Crunchyroll President Rahul Purini gave an interview to Forbes stating the anime streaming site is “not considering” using AI in their creative processes, reaffirming the importance of human creators.

However, just three months later, Necronomico and the Cosmic Horror Show premiered on Crunchyroll. At the 19:12 mark of the debut episode, the German subtitles read “ChatGPT said…” during a pivotal scene, leaving no doubt about how the translation was produced. The English subtitles weren’t much better, with lines like “Is gameorver. if you fall, you are out.”

Source: The Verge

Fans called the translations “unwatchable” and threatened to cancel their subscriptions. In response, Crunchyroll blamed a third-party vendor, stating that the AI use violated their agreement. However, the damage was already done, with many fans saying they were going back to torrented fansubs – the very thing Crunchyroll had spent years trying to make obsolete.

Why this matters for game developers

This incident carries a direct warning for anyone building games with narrative depth. In both cases, the subtitles looked like localization – structured, formatted, on-screen at the right times – while failing at the actual job of naturally and sensitively conveying what a character means, feels, and sounds like.

And more importantly, this wasn’t a one-time mistake. Even after backlash and clear statements about avoiding AI in creative workflows, the same issues showed up again. For players (and viewers), that changes how they interpret the entire product and ultimately erodes trust.

3. The Xbox German UI case

Microsoft’s Xbox CFO Tim Stuart has publicly talked about AI’s potential to solve developer challenges across localization, translation, scripting, coding, and dialogue.

But when we looked at the actual Xbox localization record in Germany, a different picture emerged. Multiple users reported that store content lacked context, the tone was inconsistent, and UI elements extended beyond their bounds.

Even in terms of context, the machine translated words like “Save” (e.g., save your game) as “Geld sparen,” which means “Save money”.

Why did this happen? Because an MT engine is trained predominantly on general internet text where “save” almost always appears in a financial context. When Microsoft used the MT for game translations, it applied that most-probable interpretation to the gaming interface where context demanded something entirely different.

On paper, these may sound like small mistakes. But when combined together for a global brand like Xbox, they’re exactly the kind of errors that break immersion and confuse users.

Why this matters for game developers

If a company like Microsoft, with all its resources and its own AI infrastructure, can ship something like this, it highlights a bigger truth: 

Localization isn’t something you can automate and forget.

The work that happens before the first word is translated

One of the least understood aspects of game localization is how much of the work precedes the translation itself. Throwing text at an MT engine or LLM skips essentially all of it. Before developers even consider translation, they must address the foundational layer: internationalization.

Internationalization is the engineering process of designing software so it can be adapted to various cultures and languages without requiring back-end code changes. This involves more than just text; it requires separating content from code, implementing Unicode support, and building flexible layouts that accommodate diverse date formats, currencies, and text expansion. Without this foundation, even the best translation will break the game’s UI.

Moving into the linguistic phase, a professional team like Context Heroes approaches the localization process with a rigorous pre-translation checklist:

  1. The first step is to analyze the source text for context, complexity, and problem areas.

    .

  2. Now, it’s time to build glossaries that include project-specific terminology for item names, character titles, game mechanics, and more, to keep consistence.

    .

  3. Wherever possible, we develop style guides that define register, voice, and tone for each character. If we have enough material in advance, this lets us identify passages that require creative solutions, helping us develop those strategies beforehand rather than encountering them line by line.

    .

  4. Expect translators to ask follow-up questions and work closely with the game developers. If a string is ambiguous, whether a character is speaking to one person or many, or if there’s any inconsistency we notice, our translators ask and incorporate the answer. These follow-up questions have often helped us surface errors in the source text itself, allowing the developer to catch problems early.

Only when every pre-translation aspect is in place does the actual localization begin. And that’s another problem with AI – it asks no questions during the translation process. It simply translates and moves on. And the more fragmented and creative the source text, the worse the final localized output. Human-based workflows have a clear edge in this area which further increases the translation quality.

So, should you use AI for localizing video games?

If you need translations for internal use, support tickets, or a rough understanding of your text across multiple languages – AI can help.

But a game with active players demands more than machines translating words in isolation.

And as we dug deeper into what developers and players actually think about completely using AI for game localization, one thing became clear from multiple Reddit discussions: the idea of fully AI-driven localization sounds great… unless it is for a real game.

One such Reddit discussion we came across talked about using a 100% AI model for game translation. And as expected, most users discarded the idea, with many reaffirming the importance of human translators while some talked about the hybrid (human + AI) approach. 

  • “How would you verify it isn’t complete nonsense without getting a translator involved?”

  • “If I still need to hire a localizing expert… why not just get them to translate it?”

  • “I’d rather have 3–5 languages done well than 10–20 done by AI alone.”

Even those open to using AI saw it as a starting point, not a solution.

Source: Reddit

So yes, you may use AI if you need a rough initial draft for your target languages.

But as a team of professional translators who have localized numerous games in multiple languages including Czech, Japanese, Brazilian Portuguese, Chinese, Italian, Korean, French, German, Ukrainian, and many more,

here’s our question to you:

AI will never know your game the way a human does. Machines generate output that looks right, but often isn’t. And when those flaws inevitably surface, the lack of accountability turns today’s “cheap” solution into an expensive long-term liability.

And it starts sooner than you’d think, with players increasingly rejecting AI slop, forcing the same human intervention you may have been trying to replace. What follows is a quality debt that’s harder to pay down than technical debt. This also manifests as the Fixer’s Tax, where Machine Translation Post-Editing (MTPE) costs can balloon to 100% of your original translation budget, as experts are brought in to repair context-blind errors, broken code variables, and UI overflows.

Add to that a growing legal risk: AI-generated dialogue often lacks copyright protection (as confirmed in 2026 rulings), meaning you could be quietly eroding your own IP valuation without realizing it. 

In the end, the hidden costs aren’t just patches and fixes. They’re permanent damage to your reputation and the structural fragility of an unprotected creative asset.

So, if you’re going to hire a professional to fix the output of a machine anyway… why not give them the complete creative freedom and be confident about your video game localization from day one?

We’ll gladly help you

Localization doesn’t have to be a guessing game. We’ll take a deep dive into your project to build a tailored localization roadmap that respects your code and your budget. Let’s talk about your game’s global future. Contact us now.

For more localization insights and strategies, feel free to browse our collection of our blog articles.

Sources