AI in eLearning

As organisations expand their global training initiatives, the demand for high-quality localised eLearning content has never been greater.

At Comtec, we frequently hear from L&D teams who want to use AI for localisation but are unsure where to start. They know AI can improve efficiency and stretch budgets further, while they also worry about quality, accuracy, and cultural relevance.

AI-driven localisation presents an exciting opportunity, but is not a one-size-fits-all solution. AI can accelerate translation, voiceover, and subtitling when used effectively. That said, human expertise remains critical to ensuring high-impact learning experiences.

This guide is to help decision-makers understand where AI can add value, its limitations, and how to implement a balanced approach that delivers high-quality, cost-effective multilingual training.

This guide provides a deep dive into AI’s role in eLearning localisation, examining:

Traditional localisation pipelines involve complex workflows. Human-led translation, manual subtitling, and voiceover recording can often be lengthy and costly—challenging when working with limited budgets and timescales.

AI-driven localisation presents a paradigm shift, semi-automating these processes with machine learning models that improve over time. However, deploying AI effectively requires a sophisticated understanding of its capabilities, limitations, and strategic implementation.

Machine translation (MT) means using artificial intelligence to enable automated text translation from one language to another.

You can use an MT engine’s output on its own, but it is more often post-edited by a human linguist. A post-editor will check for:

• Mistranslations
• Typos
• Inconsistencies
• Spelling and grammar mistakes
• Style issues

What are the pros and cons of using MT?

MT works well for:

• Technical, compliance-based, and structured learning materials
• High-resource languages (e.g. Spanish or French) with extensive MT training datasets
• Rapid prototyping of multilingual courses before final human refinement

MT struggles with:

• Courses requiring high degrees of linguistic nuance (e.g. leadership training, DEI programs)
• Languages with sparse training data (e.g. minority and indigenous languages)
• Maintaining coherence across lengthy training modules with complex terminology

Tips for managing the quality of your machine translation project

• Take care when selecting your post-editors, these should still be native speakers and subject area experts
• Support the customisation of your machine translation output with glossaries and brand guidelines, reducing post-editor effort
• Complete an upfront sample of 500 words and share with your in-market team/client for feedback, and tweak the process if necessary!

AI voiceover technology has made significant strides in recent years.
Also known as synthetic voiceover or text-to-speech, AI can convert written transcripts into an automatically generated voice that sounds as convincing as a human’s.

Just as human voiceover artists can be hand-picked, these AI-driven systems, developed by blending datasets of thousands of human voices, can generate multiple languages and even regional accents. Thus, they offer a scalable, cost-effective alternative to traditional voiceover recording.

AI voiceover is perfect for module narration and animations with multiple characters. It can quickly update and edit audio files and is available in a growing list of languages, meaning budgets can stretch further while preserving the learner experience.

Why might you want to use AI voiceover?

• Speed – Generate high-quality voiceover in minutes, not weeks.
• Scalability – Quickly localise training materials across multiple languages and regions.
• Budget – Reduce reliance on professional voice actors and recording studios, plus minimise costs for updates and revisions.
• Flexibility – Easily edit and modify content without needing a full re-record.
• Consistency – Maintain uniform pronunciation, tone, and style across multiple courses.

What are some of the best use cases for AI voiceover?

AI voiceover is ideal for:

• Localising high-volume, frequently updated training materials
• Video content with multiple characters/voices
• Reducing time-to-market for global training rollouts

Some of AI’s challenges and limitations:

• AI-generated voices may lack the emotional granularity needed for storytelling or empathy-driven training content
• Pronunciation inconsistencies, especially in context-dependent terminology
• Difficulty in handling acronyms and words with multiple meanings without manual adjustments

Expert tip: Implement AI voiceover as part of a blended strategy—using AI for content such as screen readers, and human artists for high-stakes video.

What are the most common AI voiceover mistakes?

Whatever software you use to do your AI video content, there are some specific challenges to be aware of:

Names and Numbers

• AI can struggle with foreign names, both people’s names and company names.
• AI might literally translate numerical signs, e.g. “20%” becomes “20 percentage” (rather than “per cent”).
• During QA, these will need manual tweaking to ensure they’re “recorded” correctly!

Abbreviations and Acronyms

• If your source content contains abbreviations such as “e.g.”, watch that these get pronounced correctly and not literally. For example, the Spanish abbreviation “p.ej” is pronounced as “por ejemplo” rather than just the letters.
• Acronyms might be pronounced using the target-language alphabet, but your preference could be for them to be kept as they sound in English.

Timing and Sync challenges

• Translations into specific languages (e.g. German) are often longer than English translations, meaning that speech may overlap or run too long in the German version of your video.
• Translations often need shortening to match the visual content.

How to ensure AI voiceover quality: 5 Top Tips

1. Get sign-off of translated transcripts
   Ensure your in-market team has approved the translations before you hit record – this will make the AI voiceover stage much easier!
2. Consider your cast
   AI voiceover platforms offer a wide range of voices, so make sure you’re happy with your selected one before proceeding.
3. Check pronunciation carefully
   A native-speaking linguist should listen to the AI-generated audio to catch and correct any mispronunciations.
4. Refine intonation for natural flow
   Pay close attention to AI-generated speech in long sentences, as it may have unnatural pitch drops in the middle or end of a sentence. Splitting sentences can help improve the flow.
5. Partner with AI voiceover specialists
   Work with a localisation expert experienced in AI voiceover to ensure professional-quality results that engage learners.

How do subtitles enhance eLearning?

• Improved accessibility: Subtitles make content accessible to learners who are deaf or hard of hearing, ensuring compliance with accessibility regulations such as the Web Content Accessibility Guidelines (WCAG).
• Support for multilingual audiences: AI-generated subtitles enable rapid localisation, allowing learners to engage with content in their native language without waiting for complete voiceover translations.
• Enhanced learning and retention: Reading along while listening reinforces comprehension, particularly for learners who benefit from multimodal content delivery, such as non-native speakers or neurodivergent individuals.
• Flexibility for learners: Subtitles allow learners to consume content in environments where audio is not an option, such as shared workspaces or public transport.

Some best practice tips for AI subtitling

Where automatic subtitles work best:

• Scripted instructional content with clear enunciation
• Courses with standardised terminology and phrasing
• Learning content that requires quick turnaround times

Human review is needed where:

• The training involves colloquialisms, complex jargon, or speaker variation
• Synchronisation challenges affect readability and/or cognitive load
• The content is highly regulated and exact wording is critical

Expert tip: If you want AI-generated subtitles to be as accurate as possible, prepare key terminology and brand-specific guidelines to improve their readability and quality from the outset.

And remember—no matter how good AI gets, a final human review is essential to catch any errors and ensure everything reads naturally!

It’s important to remember that AI is a tool, not a replacement.

While AI can process vast amounts of content quickly, it still lacks human judgement regarding nuance, cultural adaptation, and overall learner engagement.

Quality control remains essential to ensuring AI-powered localisation meets high standards.

The importance of human post-editing

No matter where or how you’ve used AI, human reviewers play a crucial role in:

• Refining translations to ensure accuracy and natural readability
• Reviewing AI-generated voiceover for pronunciation, tone, and clarity
• Adjusting subtitles for timing, comprehension, and linguistic accuracy

Common AI mistakes

As we’ve seen, AI can be a powerful tool for localisation, but it’s not without its pitfalls. While it accelerates processes and reduces costs, it still falls short in some areas.

Here are some of the most common mistakes to watch out for across AI-powered MT, voiceover and subtitling:

• Literal translations: AI may misinterpret idioms or context, leading to translations that miss the intended meaning.
• Robotic-sounding voiceover: Some AI-generated voices still lack emotional range and may mispronounce certain words.
• Misaligned subtitles: Automated subtitles may struggle with pacing and segmentation, making them harder to follow.

The most effective localisation strategies blend AI efficiency with human expertise to strike the right balance. A hybrid model using a blend of AI and human expert review ensures that content is produced quickly without sacrificing quality, engagement, or cultural relevance.

Different content types require different approaches. When deciding how to integrate AI, consider the following:

As AI advances, its ability to support personalised learning and rapid localisation will only increase. Organisations that embrace AI can scale their global training programs faster and more efficiently.

So here’s a recap of the key takeaways from this guide:

1. The best results come from a hybrid approach, combining AI efficiency with human linguistic and cultural expertise.
2. The right strategy depends on content type, audience needs, and quality expectations.
3. AI enhances localisation but is most effective when used thoughtfully and strategically.
4. Organisations must​​ consider cost vs. quality trade-offs; while AI reduces costs, human expertise ensures the highest engagement and effectiveness.
5. The future isn’t AI or human—it’s AI and humans working together to create engaging, high-quality learning experiences.

We hope this guide has provided valuable insights into how AI can enhance eLearning localisation. If you’re considering AI for your training content and want to balance efficiency and quality, we’re here to help!

At Comtec, we understand that integrating AI into your eLearning localisation strategy requires the right balance of technology and human expertise.

With over 40 years of experience in translation and localisation, we work closely with L&D teams, training providers, and global organisations to ensure high-quality multilingual training materials that engage learners and meet compliance standards.

Our expert linguists, localisation specialists, and eLearning professionals can help you navigate the complexities of AI-powered translation, voiceover, and subtitling.

Whether you’re looking to optimise costs, scale your training content globally, or refine your AI localisation workflow, we’re here to support you every step of the way.

Get in touch – we’d love to hear how we can help!