Why Your AI Translation Button Isn’t Working (And What To Do Instead)

If you walked the expo floor at DevLearn this year, you probably noticed the same trend we did: everyone is talking about AI translation, but almost no one is actually getting the results they expected.

One conversation with Landon in particular captured this perfectly:

“COMPANY NAME REDACTED has said we have to figure out how to “use AI”… but what does that even mean? We clicked the “translate” button. But we have no clue if it’s correct or what the user experience is.”

This wasn’t a one-off story. We heard variations of this over and over again from L&D teams across industries such as construction, manufacturing, distribution centers, higher ed, and even gaming.

The problem isn’t AI. It’s the strategy.

Ultimately, our take on AI translation might be different from what you’d expect:

AI translation isn’t the problem.

The translation strategy is the problem.

Why do we believe this?

AI translation should only be used if:

• You know why you need to translate something.
• You have the systems in place to translate something.
• You have properly prepared your AI translation engine.
• You have properly prepared your files for translation.
• You have processes for translation and localization quality assurance.
• You have processes for validation of final files.

And once you see the pattern, it becomes painfully obvious why so many “simple” AI translation shortcuts end up costing more time, more frustration, and more rework than expected.

So, let’s break down each of the real issues and, more importantly, how to solve them.

What Really Happens When You Hit “Translate”

AI tools inside authoring platforms, portals, or LMS environments all promise the same thing:
Click → Translate → Done.

But here’s what really happens:

A bilingual employee clicks the button.
The text generates.
It looks “fine” in the moment.
But once it’s published?
Once your Spanish-speaking operator or French-Canadian learner actually uses it?

The errors show up immediately.

Grammar. Register. Tone. Wrong dialect. Incorrect terminology. Compliance issues.

And the biggest one?

Loss of instructional intent.

AI translation buttons aren’t inherently bad. They’re simply blind to context, your learners, your industry, your course structure, and your accuracy requirements. Culture, compliance, safety, and many other long-term strategic goals could be at risk if when you use your AI translation button.

Why It’s Not Your Fault

AI translation inside a tool is designed to be fast, not accurate. It can’t:

• Validate terminology
• Adapt for dialects
• Maintain accessibility requirements
• Protect compliance-sensitive language
• Handle multimedia
• Manage formatting
• Respect instructional design

AI can generate language. It cannot guarantee meaning.

Which is exactly why L&D teams who rely solely on a “translate” button end up with:

• Multiple rounds of internal QA
• Hours lost chasing errors
• Confusion over which version is correct
• Distrust in the final learner experience

And in almost every conversation we had at DevLearn, teams admitted the same thing:

They don’t have the time, the bandwidth, or the linguistic expertise to fix what AI breaks.

A strategy session with a client at DevLearn, discussing the integration of AI translation to enhance multilingual user experience and streamline global communication.

The Real Fix: Workflow, Not Just Tools

Here’s the truth:
AI translation works when it’s part of a workflow, not the entire workflow.

That means:

1. Preparing your source content

If the English isn’t clear, consistent, and structured, AI amplifies every flaw.

2. Using MTPE (Machine Translation + Post-Editing)

This is where professional linguists step in to correct, validate, and shape the AI output into something usable, accurate, and instructionally sound.

3. Adding a validation step

A formal Internal Client Reviewer (ICR) or multilingual SME ensures nothing gets lost in translation, especially for compliance-heavy content.

4. Using a partner who can manage the entire process

This allows your team to stay focused on building learning, not fixing translations.

The key stages in the post-editing workflow: initial project setup, raw MT output, human post-editing process, quality review, and final delivery, emphasizing collaboration between technology and human linguists.

Why L&D Teams Need Turnkey Solutions, Not Just Buttons

The mistake we saw most often at DevLearn was simple:
Teams were trying to own translation internally.

Not because they wanted to, but because their tools made it seem “easy enough.”

In reality, most organizations:

• Don’t have full-time in-house linguists
• Don’t have multilingual reviewers for all languages
• Don’t have time to properly QA
• Don’t have a workflow for AI
• Don’t have internal standards for terminology or compliance language

And when you combine all of that with a single “Translate” button, the outcome is predictable.

Turnkey solutions exist because L&D teams already have a full-time job.

When you outsource translation properly, you’re not just outsourcing text,
you’re outsourcing:

• Workflow
• QA
• Risk
• Consistency
• Compliance
• Accuracy
• Multilingual learner experience

Which is exactly why the organizations we spoke with at DevLearn were actively looking for support, not software.

How Interpro Helps L&D Teams Succeed

Based on what we heard at DevLearn, the teams seeing the best results aren’t the ones avoiding AI.

They’re the ones using AI with structure, not instead of structure.

Interpro supports that structure through:

AI + MTPE Workflows: Using AI for speed, and professional linguists for accuracy.

Prep + Validation Packages: Especially for learning, safety, or compliance content.

Turnkey Localization: You build the English. We deliver the final multilingual courses. Fully validated, formatted, and ready for learners.

Translation Needs Assessments: For teams who know their button isn’t working but don’t know why, or teams needing expert advice and support with scaling localization systems.

Your Translation Strategy Starts Here

AI isn’t the enemy. The translate button isn’t the enemy. But relying on a button without professional guidance and a systemized workflow is a waste of money, time, and learner success. Because while you might “save with free translation” on the front end, you may very well pay in learner outcomes on the backend.

Interpro offers two resources complimentary to anyone struggling with these problems: 

1. Learn more about how teams are avoiding AI translation pitfalls with our educational guide on how to successfully implementing AI translation for learning and development.
2. Get tailored advice from subject matter experts by booking a complimentary consultation. Ask your questions, and see how leading organizations are using AI translation responsibly but without sacrificing learner outcomes or compliance.

If your internal team is overwhelmed with QA, unsure about accuracy, or starting to doubt AI-generated output, it may be time to rethink your approach. With the right processes and expert support, you can harness AI responsibly, without compromising on quality or clarity.

And if you want help building that process, choosing the right approach, or validating your AI output, Interpro is here to support you with the expertise, structure, and human oversight your learners deserve.