Automated translation: Your guide to smoother workflows

Automated translation means using technology to complete translation work automatically. 

At its simplest, this involves machine translation software that converts text from one language to another.

This is important because enterprise teams can handle large amounts of content quickly. They do this at speeds that manual work just can’t match.

For example, YouTube’s auto-translated captions are pure machine translation (MT) in action.

You’re watching The Office clips (for research, obviously), and YouTube helpfully offers captions in your language. Turn them on, and you get instant translation.

Notice anything odd? The caption reads like one long run-on sentence with no punctuation. That’s because MT is converting word-for-word without understanding the context.

A human would write this more naturally, like: ‘Call the IT guy who set it up. What’s the name of the guy in the glasses again?’

This is fine when you’re binge-watching. It’s not ideal when you’re translating legal contracts or high-priority landing pages.

Machine translation is the technology itself — the algorithms and software that convert text from one language to another. 

Automated translation manages the entire workflow, which might include MT as one piece of the translation process.

Most teams today use human-in-the-loop (HITL) or post-editing (PEMT) models — we discuss these approaches later on. Nowadays, the term ‘automated translations’ describes workflows that combine technology with human expertise.

These translation approaches exist on a spectrum:

Most enterprises work somewhere in the middle of this spectrum. They choose their automation level based on content type, available resources, and specific use cases.

The main benefits of automated translation revolve around cost control and scalability at speed. Teams can process more content faster without sacrificing quality.

When you implement the right automation, you’ll see immediate improvements across your entire workflow:

• Faster turnaround. Automation handles mundane tasks like file transfers and task assignments instantly. McKinsey research shows that 60% of employees could save 30% of their time with workflow automation.
• Cost-effective process. Your team manages higher volumes without hiring more people or paying rush fees. You avoid the premiums of last-minute outsourcing when deadlines compress — cutting operational costs by up to 30% within five years.
• Scale without breaking the process. 76% of shoppers feel more comfortable buying from sites containing information in their own language. Automated translation helps you meet global demand without overloading your team. 
• Keep quality consistent. Built-in checks and clear handoffs make sure nothing slips through, even when you’re moving quickly.
• Work in one connected system. Connect your content management system (CMS), translation management system (TMS), and machine translation engines into one pipeline. No more manual file transfers or lost translation nightmares across disconnected tools.

There are dozens of different ways to approach automated translation workflows. Some companies keep it simple, while others build more complex systems. The quality varies accordingly. 

The workflow we’ve developed hits the sweet spot between manageable complexity and high-quality results. You can tailor these key elements to fit your specific needs.

The difference between workflows that run smoothly and those that collapse comes down to how well you coordinate tools and processes. Along with assigning the right tasks to the right people.

Effective workflows share four core elements: the right mix of human oversight, smart system integration, machine translation safeguards, and automated project management.

Let’s look at each pillar and see how it helps create quality, scalable language translation.

Machine translation handles the heavy lifting. However, it can’t yet nail translation nuances like brand voice or contextual cues on its own. 

Human oversight helps fill these gaps. This ensures high-quality translations, particularly for complex language barriers or legally sensitive documents.

In human-in-the-loop workflows, linguists and subject matter experts step in when needed most. They edit high-impact content, then review for compliance and adapt the tone for different markets. 

For example, here’s how a global SaaS company might run a human-in-the-loop workflow for a new product feature rollout:

This approach delivers a few benefits:

• Humans catch context issues that AI translation misses. A machine might translate ‘bank’ as a financial institution when you meant riverbank.
• Your team avoids repetitive tasks. Instead, they focus on high-value work like brand consistency and nuanced language choices.
• Linguists maintain your brand voice across all target languages. They preserve the personality that makes your content recognizable.
• Senior linguists can oversee multiple projects at once. They review AI output instead of translating from scratch.
• You avoid the expense of full human translation and keep quality standards intact. Human oversight costs less than complete manual translation, but delivers better results than pure automation.

The key is to find the right balance for your content types. 

High-stakes materials, like legal documents, need close human oversight. Internal communications, though, can rely on machine translation with just a light review.

You need a smart integration ecosystem that connects your CMS, translation technology engines, QA tools, and TMS into one seamless workflow.

Without it, your team just wastes time on manual handoffs. One moment, they’re exporting files from the CMS. Next, they’re jumping into another system to check progress and re-upload translations.

It’s a clunky, error-prone process that turns simple updates into headaches.

Integrated systems clear these friction points. Translated content flows automatically from creation to publication. Project managers see status updates without chasing down team members.

Translation solutions like XTM Cloud make this possible with integrations. These connect your existing tech stack into one smooth workflow. Content moves between your platforms, eliminating manual file transfers and duplicate data entry.

Here’s how this works with popular business tools:

• Adobe Experience Manager. Marketing teams handle website translations directly from their digital experience platform. No need to export files or switch systems.
• Contentful. Content flows from your headless CMS straight into translation workflows. Then, it publishes automatically when linguists complete their work.
• Marketo. Email campaigns and social media content move smoothly through localization. This way, they don’t disrupt your marketing automation sequences.
• Jira and GitHub. Development teams sync UI strings and updates. They do this between code repositories and translators in real time.

For teams with complex tech stacks, XTM also offers flexible API access. So they can customize integrations to match your exact workflow.

For example, language service provider Hunnect used XTM APIs to connect directly with its client systems and invoicing platform. This cut manual file transfers and saved its team 50–100 hours per week. The LSP now processes more projects with the same staff.

Bottom line: When your systems connect properly, translation becomes a natural part of your content workflow. Your team can focus on translation quality instead of file management.

Raw MT output can butcher your brand voice, but the right QA tools can step in to protect it without compromising speed.

Research shows that machine translation still struggles with domain-specific terminology and rare technical words. Not to mention hallucinations when handling unfamiliar content.

Enterprise automation adds quality control layers to neural machine translation. These layers adapt based on the content you are translating.

This balance between speed and quality is key, as Sara Basile, Product Director at XTM, explains:

Not all content needs the same level of human oversight. 

Raw output might be enough for high-volume, low-risk content. For anything customer-facing or brand-sensitive, you need human review.

Use this breakdown as a starting point for your own workflow decisions:

These are starting points, not rigid rules. Your content strategy should guide these decisions. 

For example, a fintech company might route all customer-facing content through human translation. On the other hand, a SaaS startup could use MT with light editing for most marketing materials.

Note: Some tools, like XTM, can be configured to meet specific legal requirements for translations to be accurate and compliant with relevant laws and regulations. XTM’s technology management features help ensure correct and consistent use of legal terms.

AI-powered quality assurance tools make the difference here. For example, XTM AI builds these safeguards directly into your workflow. Here’s how it supports translation teams:

• Generates accurate translations from similar past content using translation memory to maintain consistency across projects. You can stop translating from scratch. 
• Language Guard scans 90+ languages for harmful or offensive terms before publication. The system automatically flags problematic language and suggests corrections. 
• Intelligent Score provides AI-powered quality scoring for each translation segment. Helping linguists focus on problem areas first and speeding up the review process.
• Intelligent Workflow automatically routes content based on quality insights and performance data. The system triggers appropriate QA steps without manual intervention.
• Terminology Management enforces approved terms and builds on your translation memory.

XTM also connects with top MT engines like DeepL and Google Translate. Letting you choose the best engine for every language pair.

Through the XTM AI Control Center, you control exactly how much AI support you want. Toggle specific functionalities on or off based on your team’s needs.

Bottom line: When MT has proper safeguards, you can use it confidently across more content types. The technology handles volume while your team ensures quality where it counts.

Manual project setup kills productivity when you manage hundreds of translation projects monthly. Smart automation takes project chaos off your plate.

Even on their most productive days, 36% of translators can only translate between 1,500 and 3,000 words per day.

Teams waste hours creating projects they then assign to linguists, along with routing files — draining valuable admin time.

Modern automation fixes this with intelligent workflows. They manage everything, from starting projects to assigning linguists.

Here’s how automation handles the repetitive work that bogs down project managers:

• Rule-based triggers monitor your content sources 24/7. They launch projects automatically when conditions are met. For example, creating new market translations for EMEA whenever Spanish product documentation updates. 
• Auto-delivery sends completed translations directly back to your CMS, marketing platforms, or code repositories. This happens without any manual human intervention. It also cuts the upload/download delay that typically adds 2–3 days to project timelines. 
• Continuous localization creates steady workflows. These replace the weekly translation batches that create feast-or-famine workloads. The continuous project automation of XTM generates cost estimates and manages project history automatically. 

Once automation takes over the repetitive tasks, your team can:

• Handle more content without hiring new project managers
• Eliminate 2–3 day delays from manual file transfers
• Scale content updates without administrative overhead
• Prevent translator burnout with consistent workflows instead of batch processing

Bottom line: When automation handles project setup and delivery, the chaos disappears. Teams process twice the content with half the stress. The constant last-minute scrambles become rare exceptions.

Acolad faced serious scale challenges with its offline CAT tools and local translation assets. Content lived in silos, and it wasn’t accessible to its global team of over 2,500 employees and 20,000+ linguists.

Teams had to constantly repeat tasks when deploying licenses and upgrades. As the business grew and new companies joined the Acolad group, manual processes became unsustainable.

With the automated workflow engine of XTM Cloud, the LSP leader solved these scale problems.

Acolad used the platform’s presets and templates to automate project setups. This way, it could easily replicate configurations for future documents.

The results were:

• Automation replaced manual task management wherever appropriate. This made the localization process workflow much simpler. 
• Project management tasks became easier to organize across its global operations
• Teams could collaborate more easily across multiple countries and time zones
• Teams could monitor and improve performance in a much more responsive way

As Vincent Rigal, CAT Tools Products Owner at Acolad, puts it: “XTM Cloud forms a big global ecosystem of seamlessly connected accounts to which thousands of users connect daily. Overall, the result is better quality with fewer resources.”

There are five core tool types — TMS platforms, MT engines, QA tools, and project management solutions.

Here’s how each component contributes to workflow automation:

Choose tools that integrate well. Look for the best translation management systems with built-in connectors to your existing systems to set up seamless workflows. 

For example, XTM Cloud offers more than 60 integrations with popular CMSs as well as marketing platforms and development tools.

XTM provides everything you need for automatic translation in one connected platform.

Managing translation services with disconnected tools creates chaos. Teams jump between their TMS, MT engines, quality checkers, and project management platforms. Meanwhile, updates fall through the cracks, and every handoff becomes a potential failure point.

The XTM ecosystem combines several tools into an integrated platform for enterprise translation automation. 

Each component handles different aspects of your localization strategy:

• XTM Cloud is the central translation management hub. It handles projects from creation to delivery through automated workflows, plus 60+ integrations and AI-powered quality translation tools. Connect it with your existing content systems to handle the operational complexity of enterprise-scale localization.
• XTM Workbench provides linguists with a purpose-built CAT environment. Its translation features include visual context, in-layout previews, and translation memory integration. Translators instantly see exactly how their work appears in the final product.
• XTRF manages the business side of translation operations. It manages vendor relationships, project pricing, invoices, and financial reports, letting you automate everything from initial quotes to final payments. 
• Rigi handles software localization specifically. It provides developers and translators with live visual previews of UI strings, which show how the strings look in their real interface context. It removes the back-and-forth questions that typically slow software localization.

These components work as one connected ecosystem rather than separate tools. Data flows automatically between systems, and teams manage everything from a central point.

This means you can build the exact automation setup your organization needs. You don’t have to worry about the integration headaches that come from mixing providers.

To start automated translation, follow this five-step process: audit your workflows, map your tech stack, pilot with low-risk projects, ask your team for input, and choose the right TMS.

Here’s the detailed breakdown for each step:

Don’t try to automate everything at once. Find the biggest time sink in your team and fix that first. 

Johnson Controls took this approach when it faced manual workflows and chaotic vendor management across 150 countries. This created extended timelines and rising costs.

The smart building technologies firm used XTM Cloud to automate file transfers and project assignments — its major pain points. Within months, it cut turnaround times by four weeks and gained full control over its translation operations.