7 of the best AI translation tools for enterprise localization in 2025

AI translation tools convert text between languages automatically using machine learning. 

Most modern AI applications are more useful for localization than basic, rule-based translation programs as they:

• Understand context 
• Adapt to a range of use cases (e.g., marketing content or web development)
• Improve continuously

For example, a recent XTM Cloud update included OpenAI integration and XTM AI SmartContext for delivering on-brand, professional translations with minimal effort.

Versatile artificial intelligence like this helps enterprises translate all kinds of content, from marketing campaigns to product documentation. All without hiring new staff or delaying market entry.

Imagine an industrial tech manufacturer launching new electronic components in 30 countries simultaneously. It’s a huge logistical operation, even before you add translating to the mix.

But with AI generating baseline translations (i.e., doing the heavy lifting), the company can direct its human expertise where cultural precision is hardest to achieve or matters most. 

This speeds up the launch and helps to build trust in the new markets. Most importantly, though, it boosts revenue and profitability.

Some providers will tell you their AI alone can solve all your translation woes. They’re lying.

The truth is that AI only works as part of a high-quality, effective localization strategy. One with clear, achievable objectives and well-organized project management backed by human translation expertise.

When you understand what AI translation can do for your business and where it falls short, you can set achievable implementation goals and get a much better ROI.

Our all-in-one localization hub uses AI with other features to help enterprises with translation, project and vendor management, and software localization.

It’s perfect for global brands that need to manage complex localization processes quickly and often without compromising quality.

XTM can save users up to 2,000 hours in translation time while achieving 98% accuracy, significantly reducing time to market.

Our suite of products use AI in their own way to grow efficiency.

Here’s some of what XTM Cloud’s AI can do:

• Generate high-quality translations from fuzzy matches with consistent and accurate results
• Detect non-inclusive or inappropriate language, protecting your brand’s integrity
• Flag segments that don’t meet your quality standards, allowing faster fixes
• Automatically place formatting tags in translated content to save time and reduce errors

Its visual context features also show in real time exactly how your translated content will appear to users, so you can address issues before going live. Preview translations across app interfaces, web pages, or technical documentation and keep your professional reputation intact.

There’s support for various content formats, like Adobe InDesign and Google Docs files.

Meanwhile, integrations with CMS, marketing, developer, and design platforms will help you build a powerful tech stack.

Having all these features in a TMS helps many global enterprises save money and grow efficiency. 

Andreas Ljungstrom, Senior Manager of Solutions Architecture at XTM, gives IKEA as one example:

“For IKEA, each country operates with a certain level of autonomy, but they saw significant saving potential in centralizing their localization system. Now localization managers in all countries — Italy, Brazil, Japan, wherever — use the same system, leveraging shared repositories and databases.”

XTRF is a business workflow and project management solution for LSPs and localization teams.

It improves project outcomes by automating vendor selection based on past performance and matching the right translators to each job. It also effectively forecasts costs and timelines.

Let’s say your marketing team needs product launch content translated into 10 languages quickly. The system can automatically assign the best-performing linguists for each language and estimate the delivery date. It literally saves hours of manual coordination. 

These capabilities grow revenue through better resource allocation and by pre-empting productivity bottlenecks.

Rigi is a software localization tool that helps SaaS and tech companies translate products with greater accuracy and context, shortening their time to market.

The software minimizes translation errors by showing marketing, product, and development teams exactly how content will appear in their product environment — whether web and mobile or desktop.

Rigi automatically pulls text from software and provides in-context previews to catch issues early (e.g., truncation or layout breaks). This helps teams adjust layouts to accommodate linguistic changes before release, ensuring translated interfaces work properly and look great.

Here are five ways that the cloud-based XTM hub makes your business more efficient and informed:

• Automatic content synchronization across systems with intelligent file handling
• Cross-platform analytics for insights into the whole localization process
• Integrated AI that learns throughout your localization workflows, becoming more valuable to you and your team
• Effortless quality management with AI-assisted error detection for eliminating embarrassing translation faux pas
• Seamless alignment between translation projects, vendor management, and software localization — use all the tools as one platform or pick the one you need

A single tenancy option (where the customer has their own dedicated server environment instead of sharing with other cloud users) also separates XTM from other tools in the market.

This approach combines the security and performance you’d get from on-premise solutions with cloud flexibility. It’s ideal for balancing high translation outputs with regulatory compliance.

Who XTM is best for: Large enterprises looking to translate lots of content faster while maintaining strict quality control. The platform’s centralization and workflow automations are invaluable for companies managing high-volume, complex content for multiple markets.

XTM pricing: XTM Cloud plans start at $16,500 per year for unlimited users, projects, templates, and workflows. Our tailored pricing is based on volume and specific requirements.

This might be a bigger investment than some tools require, but it pays off quickly: XTM users have cut localization costs by up to 60%, shortened time-to-market by up to 80%, and boosted output by 250% without adding resources.

A user’s view on XTM: “XTM is incredibly practical when it comes to TM and terminology management, including in collaboration with the customer. TMs and terminology can be effortlessly imported and exported. The user interface is super easy to use for translators and project managers alike. The option to create templates is also a very useful feature that can save a lot of time when creating projects.

“XTM support is always quick to respond and help, which we very much appreciate. The webinars provided by XTM also contain a wealth of practical tips and information.” — Verified XTM user, via G2.com

DeepL is a neural machine translation service. It prioritizes translation that preserves original meaning and flows naturally in the target language. 

The company’s claim to offer “the world’s most accurate translator” is subjective, but the tool has its fans.

The DeepL Translator comes as a free online service for occasional users. A subscription-based DeepL Pro version has more comprehensive features to suit businesses.

DeepL uses neural networks to understand context and generate translations. In simpler words, these are computer systems designed to replicate human brain activity.

Key features of DeepL include:

• Document translation options. Handles many file formats, including PowerPoint and PDF, and aims to protect formatting across them all.
• Glossary function. Allows users to customize translations with specific phrasing and terminology. Useful in niche industries.
• API access. Shares data with other systems and applications (e.g., Google Workspace and ZenDesk).
• Data security options. The Pro version provides extra protection for sensitive content.

Who DeepL is best for: Those looking for natural-sounding translations in common European languages (e.g., French and Spanish) may find DeepL suitable. DeepL supports fewer languages than some competitors: around 30 at the time of writing, compared to 887 for XTM.

DeepL pricing: DeepL’s free version is limited to one user and short on security measures, so it won’t suit enterprise translation. DeepL Pro starts at $34.49 per month for teams and individuals, with tiered business plans based on translation volume. Most large companies will need to look at enterprise pricing for custom solutions.

A user’s view on DeepL: “DeepL provides excellent German-English translations. It’s incredibly convenient that you can translate text with HTML tags intact, making it easy to work with website code. Additionally, the API integrates seamlessly with WordPress, allowing articles to be translated with just one click. However, the translation quality for Russian and Ukrainian languages is notably lower.” — Verified DeepL user, via G2.com

Google Translate is one of the world’s most widely used machine translation services, probably because it targets consumers and is so easy to access. 

The basic app can translate more than 200 languages and integrates with many Google products (e.g., Android smartphones, Google Docs, Gmail, etc.).

While it puts consumers first, Google also offers enterprise translation capabilities through Google Cloud Translation (limited to “more than 135 languages”). 

This includes Translation API for programmatically translating websites and apps, along with other systems, in real time. Reviews suggest the program handles widely spoken languages well, but quality varies with niche pairs and dialects. 

Like most Google products, Translate benefits from plenty of incremental improvements. Recent updates have enhanced context awareness and improved accuracy in many language pairs.

Other key features of Google Translate include:

• Broad language support. Covers more than 200 languages (fewer with Google Cloud Translation), including many low-resource languages.
• Document processing. Translates text from various document formats while preserving layouts.
• AutoML Translation. Enterprises can develop custom translation models for specific domains.
• Mobile integration. Offers offline translation capabilities through mobile apps.

Who Google Translate is best for: Organizations that need decent language coverage and fast access, especially for niche language pairs (Lingala and Quechua, anyone?). As well as those looking for a simple but cost-effective translation tool to use on the move.

Google Translate pricing: The consumer version of Google Translate is free. Google Cloud Translation has pay-as-you-go pricing from $20 per million characters (after some introductory credit discounts). AutoML Translation has separate pricing based on training and prediction hours.

A user’s view on Google Translate: “[Google’s Translation] API supports both neural machine and customizable translation models, which is a big plus for businesses looking to tailor translations to industry-specific terminology. While the API performs well for widely spoken languages, the quality can be hit-or-miss with niche languages or dialects. Additionally, customization options are somewhat limited in comparison to other enterprise-level translation solutions.” — Verified Google Translate user, via G2.com

Smartcat blends translation management with a linguist marketplace, making it a potential hybrid option for companies needing both AI translation tech and ad-hoc human support.

The system provides workflow automation and collaboration tools that include project management functions. It also offers AI-enhanced machine translation. 

Reviews suggest these features are sometimes slow to load, so bear this in mind if you’re keen to work fast.

Smartcat processes content using a range of third-party machine translation engines (e.g., Google Translate, Baidu, Microsoft Translate, etc.). You can choose which to use manually or let its AI pick the best fit for your language pair.

The marketplace connects companies with freelance translators, language service providers (LSPs), and subject matter experts. All parties can be assigned projects within the platform.

Smartcat’s other key features include:

• Translation memory and glossaries. Stores previously translated content and terminology to save some time.
• Video translation. Creates multi-language transcripts, subtitles, and dubbing for MPEG and MP4 files using generative AI.
• Automated workflows. Aims to speed up translation projects from submission to completion.
• Vendor management. Handles payments to freelancers and agencies from a single account, reducing app-switching.

Who Smartcat is best for: Companies without in-house translation teams that are keen to manage external resources more efficiently. Organizations with variable text translation needs that can’t justify hiring full-time translation staff may find the marketplace helpful.

Smartcat pricing: Smartcat plans start at $99 per month for businesses (for basic functionality with tight usage limitations). Custom enterprise pricing can remove restrictions for larger organizations.

A user’s view on Smartcat: “It was and still is a tool that streamlines the translation processes we request in the company. The translations are fast and 99% accurate because the remaining 1% is a literal translation that can be fixed in the same software. Sometimes, the software indicates that its engines are overloaded after starting translations, [which can make] translations take longer than an hour to work.” — Verified Smartcat user, via G2.com

Could we discuss AI tools without including ChatGPT? 

OpenAI’s large language model, or LLM, translates text within its broader conversational capabilities, although it isn’t built for localization.

The app, accessible through browsers, desktop, and mobile apps, is useful for simple, ad-hoc language tasks like: 

• Reading foreign-language emails 
• Understanding competitor content
• Proofreading some content post-translation

Here’s what it looks like in translating action:

There’s no official information on ChatGPT’s linguistic abilities (because it’s not a real translation tool), so we asked the app directly. 

We learned it translates between “roughly 100” different languages and its quality varies:

The app can explain cultural nuances or provide extra context on request, although this manual process won’t be efficient enough for companies translating at scale.

ChatGPT can adapt translations to specific tones or styles, too. But again, it takes some manual prompting. 

For example, you might ask it to translate a document and make it “more informal” or “friendlier” at the same time.

ChatGPT lacks the specialized features many enterprises need. For instance, translation memory, glossary management, and even workflow capabilities. 

It also won’t integrate directly with CMS or other business apps without custom development.

That said, there are still a few reasons you might look at ChatGPT for basic translation:

• Context-aware translations. Understands and maintains context from conversation history.
• Adaptable style and tone. Adjusts translations to suit the desired formality or audience.
• Multi-purpose functionality. Combines translation with other tasks like coding and content creation or summarization.
• API access. Integrates with lots of other systems through OpenAI’s API (requires enterprise plan and custom development).

Who ChatGPT is best for: Small teams and individuals that need infrequent email, message, or short document translations. It’s fine for internal communications but way too limited and inconsistent for customer-facing content or large-scale translation projects.

ChatGPT pricing: There’s a free plan with limited features (usage and model restrictions). ChatGPT Plus costs $20 per month for individuals. The much costlier Team and Enterprise plans have extra security and volume capabilities to suit larger companies.

A user’s view on ChatGPT (for translation): “From my experience and feedback I’ve gotten from native linguists, ChatGPT’s translations are still too literal. When you ask ChatGPT for a translation, it seems its default is to provide a literal translation. That means that the word order is similar to that of the source text. While it’s correct and understandable, it sounds awkward; it hasn’t been adapted in form and flow to the target language.” — Localization professional, via ‘Life, Language, and Localization’

Crowdin is a cloud-based localization management system for projects involving mobile or web content and software.

While its focus is project management, Crowdin also offers machine translation with memory and glossary support. Reviews suggest the UI has a steep learning curve, however.

CrowdIn is one of the few platforms to openly promote video game localization as a use case, having supported high-profile titles like Minecraft and Counter-Strike 2.

Just like Rigi, Crowdin integrates with dev tools and repositories like GitHub and Bitbucket. This allows automatic synchronization between code changes and translations, helping to maintain consistent localization across product updates.

Other key features of Crowdin include:

• In-context translation. Shows translators how text will appear in the application.
• Version control. Tracks changes to help manage multiple iterations of translated content.
• Crowdsourcing function. Allows for community translation contributions when desired.
• QA checks. Identifies possible issues, like inconsistent terminology or missing translations, before they impact users.

Who Crowdin is best for: Software companies and development teams looking to localize digital products across multiple languages, including video games. Its specialized gaming focus suits targeted projects, though enterprise solutions like XTM better serve broader corporate translation needs.

Crowdin pricing: Crowdin’s free plan covers one project with up to 60,000 hosted words and up to two users. It also requires you to donate translations to the company’s translation memory. Premium plans start at $48 per month, increasing based on the number of projects, users, and words translated.

A user’s view on Crowdin: “The platform supports a wide range of file formats and integrates seamlessly with various development tools, making it incredibly efficient for managing multilingual content. The initial learning curve can be somewhat challenging for new users who are not familiar with localization platforms. While the interface is generally user-friendly, navigating through some advanced features can feel overwhelming without proper guidance or prior experience.” — Verified Crowdin user, via G2.com

Trados Studio is an established desktop-based translation software. It has comprehensive features for translation professionals and enterprises that want extensive customization options, although the information-heavy interface won’t suit everyone.

While Trados was originally desktop-focused, recent versions offer cloud integration through the RWS Language Cloud to allow file sharing and online collaboration. It’s a hybrid approach that provides flexibility for companies with varied work environments — the kind you get from many other cloud solutions.

Trados Studio integrates with a range of MT engines and lets users adapt these to improve performance for certain language pairs or subject areas.

Trados’ other key features are:

• Customizable translation memory. Stores and reuses translated content with extensive configuration potential.
• Offline capability. Functions without an internet connection for secure environments.
• File format support. Handles a range of file formats, including specialized desktop publishing files (much like XTM).
• Quality assurance tools. Identifies errors, including inconsistencies and format issues, for smoother projects.

Who Trados Studio is best for: Large businesses with established translation departments and complex file formats or customization needs. Regulated industries requiring strict quality control can also benefit. 

Trados Studio pricing: Trados offers multiple licensing models, including subscription packages starting at $185 per month. There’s enterprise pricing for multi-user deployments, with quotes available on request.

A user’s view on Trados Studio: “[It has a] user-friendly interface and easy filters to display only certain segments. The project management side was completely lacking, at least when our company used the software. We switched to XTM which makes allocating jobs so much easier. With XTM there is no need to send files by mail either, everything is already in the software in the Cloud.” — Verified Trados Studio user, via G2.com

All good AI language translators have their selling points. 

The XTM suite is comprehensive and versatile as well as connected. Google Translate offers consumer-first simplicity. ChatGPT can do much more than translate text (it does lots of things better, in fact).

But what about the non-negotiables?

Whether you’re choosing from our guide or already have a shortlist, don’t let grand marketing claims distract you from the following must-haves:

This guide might be all about using AI for translation, but effective localization still requires a lot of human intervention.

The more admin your chosen solution can complete, the more time your team will have to review and collaborate on translations, plus manage feedback from local users.

With that in mind, look for translation AI tools that offer:

• Automated content synchronization across systems (e.g., between your TMS and CMS)
• Configurable approval workflows for different markets and content types
• Role-based permissions that suit your company’s structure (meaning team members don’t need to waste time requesting access)
• Vendor management capabilities, like automatic project assignment 
• Cross-platform connectivity between translation projects, vendor management, and software localization

For example, using XTM Cloud to automate localization workflows helped Johnson Controls cut costs and reduce project turnaround times by four weeks.

AI is great at translating content, but even the best applications can struggle with complex cultural nuances and hyper-specialized idioms. 

This limitation makes reliable quality assurance tools essential.

Your system should have:

• Context-aware translation capabilities for various content types (e.g., XTMs SmartContext technology fine-tunes machine translations using your translation memories)
• AI-assisted quality scoring and error detection
• Terminology management to maintain brand-specific language
• Customizable QA checks that stop minor errors from snowballing

Take Farfetch’s story, for example. The global fashion retailer used our powerful translation memory, glossary tools, and QA checks to improve translation consistency and maintain its brand voice.

Enterprise translation tools must be able to handle large datasets, product catalogs, and global campaigns efficiently while maintaining strict security standards.

These criteria are particularly important for companies working with sensitive or regulated content, such as life sciences and financial services businesses.

Security features to look for in AI translators include:

• Compliance with GDPR, ISO 27001, and SOC 2 standards
• Single tenancy options that provide dedicated server infrastructure for maximum security (this won’t be necessary for all users but will suit some deployments)
• Granular access controls for all user types and content categories
• Detailed audit trails and version histories
• Data encryption

For instance, the access rights security of XTM helps language solutions firm Acolad enforce its need-to-know policy around client data. This way, it can protect both sensitive information and trust.

The most useful AI translation tools improve over time, based on human linguists’ corrections and feedback as well as general product updates. 

This machine learning approach means your translation technology becomes more valuable the longer you use it. And keeps up with broader technological advances.

For example, effective systems will:

• Automatically update their translation memory with approved content (including learning from corrections)
• Adapt to your brand voice and industry terminology
• Apply context-specific translations based on previous content
• Provide analytics data to show improvements

Adding adaptive machine translation to its workflow helped Tilde manage growing content volumes. The technology constantly learns from translator corrections, helping the LSP’s team to work faster without affecting quality.