Tackling misinformation in the age of AI

With the rise of AI-driven content, ensuring accuracy and combating misinformation has become a top priority. Several key sessions looked at AI quality and user experience, and shed some light on ways technical communicators can proactively safeguard against misleading content.

Countering fake news through better UX

In a session on misinformation, Ray Gallon from The Transformation Society argued that effective UX strategies can help counter fake news. He stressed that presenting accurate information alone is insufficient; communicators must appeal to users’ emotions. Techniques like user journey mapping and inferential learning help create engaging, accurate narratives without sensationalism.

Addressing AI errors at the source

Regina Preciado’s session “Your AI Isn’t broken, your content is” highlighted the integral role of content quality in enhancing AI-generated documentation. Looking in particular at AI hallucinations and inaccuracies, Regina honed in on poorly structured content, advising businesses to establish a single source of truth approach to all of their documentation and content – no matter its intended audience.

She emphasized how always referring to an original source helps AI systems provide consistent, reliable outputs, and how reliable AI can help secure trust and future investment internally.

Enhancing AI accuracy with ontologies

Prof. Dr. Martin Ley and Max Gärber from PANTOPIX emphasized the importance of ontologies—structured frameworks that define relationships between concepts—to improve the accuracy of generative AI. Product ontologies serve as a foundation for large language models (LLMs), ensuring they interpret product data more reliably.

For communicators, this means that using structured data frameworks can help mitigate errors in AI-powered chat applications, adding precision to user interactions and reducing misinformation risks.

Multiple sessions this year stressed the importance of structured, rigorous data inputs when training AI and building processes. From proactive content verification to UX design, it’s important that companies plan ahead in order to create and maintain credible, reliable AI-generated communication.

Maximizing ROI and quality in global communications

As localization becomes a more crucial component of internationalization strategies, ROI is increasingly on the agenda, with more financial eyeballs on the function than ever. Beyond typical localization metrics, several speakers discussed how to quantify ROI more effectively, and how financially savvy approaches can actually impact the user experience and the fortunes of an entire business. 

Linking localization to ROI

In an interesting session linking localization efforts directly to business goals. Translate.One’s Quality and Product Manager, Christiane Schaeffler highlighted the need for both quantitative metrics (like market expansion and customer retention) and qualitative indicators (such as enhanced user experience).

By aligning around customer satisfaction, rather than relying on siloed metrics like turnaround time, it becomes possible to build more compelling business cases for localization investments, and fine-tune strategies to improve content relevance and impact.

Enhancing accessibility with LangOps

Vivien Krämer and Jochen Hummel gave a wide-ranging intro to Language Operations (LangOps). LangOps combines machine translation, advanced text analytics, and multilingual knowledge systems to optimize communication efforts at scale. Exploring its recent adoption at Roche Diagnostics, they explained how LangOps has enhanced content accessibility across languages, and proven useful in standardizing regulatory compliance. By unifying language resources, LangOps supports product localization and also assists with search and customer support, making it a versatile enterprise tool. 

Tracking localization ROI, leveraging AI-powered LangOps, and fostering cultural competence are crucial for ensuring effective global comms. This approach ensures that localized content meets quality standards while resonating with diverse audiences, maximizing both engagement and ROI.

Optimizing documentation processes and efficiency

As content grows more complex, documentation teams face the challenge of managing reviews efficiently. These sessions shared techniques to streamline review cycles, embed quality assurance early, and prioritize sustainable content design.

Tackling review challenges in technical documentation

Dr. Saul Carliner from Concordia University identified five common issues in documentation reviews, such as contradictory feedback and unresponsive reviewers. He recommended solutions like setting clear review guidelines and holding pre-review meetings to clarify expectations, creating more relevant and timely feedback. Carliner also highlighted the importance of cultural competence, helping communicators assess cultural sensitivity, ethical considerations, and adaptability for inclusive, globally resonant content.

Embedding quality assurance early: The shift-left approach

Valentina Turra and Daniela Fleck from Philips shared their “shift-left” approach to localization, which emphasizes proactive quality checks early in content development. This strategy allows teams to resolve issues early, producing clear, consistent documentation that meets user needs. At Philips, this approach has improved documentation quality and streamlined user experience.

Promoting sustainable UX in documentation

Nolwenn Kerzreho from Madcap Software advocated for minimalist, sustainable content design to reduce information overload. By focusing on essential information, technical communicators can create clearer, more user-friendly documentation, enhancing engagement through simplicity.

All of these sessions underscored the value of refined review processes, early quality checks, and sustainable design principles, enabling teams to produce efficient, user-focused documentation that improves workflows and user experiences.

Enhancing user experiences with data

Long used for customer-facing applications, data-driven insights are now changing the game for technical documentation. Several sessions illustrated how technical communicators can use data, JavaScript, and tailored workflows to create content that resonates with today’s users.

Enhancing documentation through data

Rachael Hewetson and Sophie Sofce Kohl from SAP highlighted how data-driven insights guide documentation improvements. By analyzing metrics like page views and search trends, SAP identifies content gaps and reduces support requests. This approach enables communicators to prioritize updates that directly address user needs, resulting in documentation that is both relevant and user-friendly.

Empowering writers with JavaScript

Collibra’s Ken De Wachter encouraged technical writers to learn basic JavaScript to add interactive elements such as tabs and dropdowns to documentation. These elements make content more engaging and user-friendly. De Wachter emphasized that even a small amount of coding knowledge can enable writers to meet modern expectations for dynamic, interactive documentation.

Customizing DITA DocOps for corporate efficiency

Dia Daur from A-Jour-Net Inc. discussed how corporate teams can optimize their DITA (Darwin Information Typing Architecture) workflows. Customizing DITA DocOps allows for efficient content management, enforcing taxonomy standards, simplifying navigation, and facilitating mass updates. This approach ensures content consistency and adaptability across various channels, which is essential for large teams.

Combining data insights, interactivity, and optimized workflows empowers technical writers to deliver engaging, user-centered content. These methods help meet the high expectations of today’s users by enhancing the usability, relevance, and accessibility of documentation.

Leveraging simplified language standards

Clarity in technical documentation is especially important when dealing with multilingual operations teams. A pair of useful sessions highlighted how language standards like Simplified Technical English (STE) support clearer communication and reduce translation errors.

Writing procedures in Simplified Technical English (STE)

Daniela Zambrini and Orlando Chiarello from eXeL8 and STEMG introduced ASD-STE100, a controlled language standard designed to simplify technical English. They outlined STE’s structure and vocabulary limitations, showing how it eliminates ambiguity for readers. Through practical exercises, attendees saw how STE enhances understanding for non-native speakers and translators, enabling them to convey technical details accurately.

STE’s role in AI-assisted content creation

Orlando Chiarello also joined Jennifer Bennor to discuss the importance of STE in AI-driven content creation. As AI increasingly supports translation and content generation, standards like STE are essential to maintain clarity. By minimizing vocabulary and simplifying structure, STE helps prevent AI misinterpretations, ensuring content remains accurate and consistent across languages.

Simplified Technical English (STE) plays a vital role in creating clear, translatable documentation. Controlled language standards like STE are critical for ensuring accuracy, particularly as AI becomes more involved in multilingual content delivery.

This year’s tcworld conference emphasized the need for structured frameworks, from UX design to STE, in managing misinformation and leveraging AI effectively. Sessions underscored the importance of measuring localization ROI, adopting LangOps, and nurturing cultural awareness to ensure content resonates with diverse audiences. Additionally, prioritizing documentation efficiency and integrating data-driven insights and interactivity were highlighted as essential steps for technical communicators aiming to meet the demands of a globalized digital landscape.

1. AI: Revolutionizing Localization Processes

It should be no surprise that the bulk of the LocWorld52 sessions covered AI in some capacity.

At Phrase, we’ve spoken extensively on the topic recently, and as the technology advances, it should be no surprise that it is set to affect the role of localization professionals ever more acutely.

While many talks touched on AI, several stand-out sessions looked at more niche areas where automation and AI can assist. 

• • AI for Low-Resource Languages: In a standout session, Sheriff Issaka and Tumi Samuel-Ipaye from the African Languages Lab shared how AI and NLP are bridging language gaps across Africa.

    They emphasized that high-quality AI translation for under-resourced languages requires a balanced combination of machine learning and human expertise.As an example, the speakers looked at the dialectical range in two languages – Igbo and Swahili.

    With so many small incremental changes to languages across a relatively small geographical area, AI is able to apply data points at a scale which previously would have been impossible.

    Techniques like transfer learning, taking a pre-trained model and adapting it to a new, related task or dataset and human-in-the-loop learning, where humans actively participate in the model training process, labelling data, verifying predictions, and providing feedback, are crucial. These approaches help ensure that digital transformation in Africa respects linguistic and cultural diversity.

• • Generative AI’s Impact on Project Management: Marilyn Dickinson and Aki Hayashi from Dell Technologies spoke about the ways AI is transforming project management.

    Using AI-driven frameworks, Dell has enabled managers to predict delays, allocate resources efficiently, and automate workflows, fostering innovation and efficiency in complex, multilingual projects.

    By optimizing workflows, Dell has been able to significantly increase its language offerings – from three to 50 – so that it can communicate more effectively with more customers.

  • Integrating LLMs with Existing Systems: In a session by Jonas Ryberg from Centific, the focus was on integrating Large Language Models (LLMs) into established localization systems.

    Instead of replacing current tools, companies are strategically augmenting them with LLMs to enhance functionality while maintaining consistency across existing workflows.

These discussions collectively underscored the importance of implementing AI thoughtfully—leveraging its capabilities without overlooking quality, cultural relevance, and the irreplaceable human touch.

2. Multimedia Localization in the AI Era

Multimedia localization, particularly in gaming and children’s content, received special attention this year.

As multimedia experiences grow more complex, the stakes for cultural accuracy and ethical responsibility have risen significantly, with greater rewards for getting it right, and harsher penalties when things go awry.

• • AAA Game Localization: Patrick Görtjes from Massive Entertainment gave an insightful look into the localization process behind Avatar: Frontiers of Pandora. 
    Embedding localization teams within game development from day one ensures that every audience experiences the game as authentically as possible, with correct cultural references.
    As well as enhancing user engagement, this early-access approach is helping to reduce the costs of reworking and duplicating content later on.
  • Localizing for Young Audiences: Sham Albdour of Gamester Kids and Marina Ilari of Terra Localizations explored the high-stakes nature of children’s content localization, which has strict compliance demands.
    For young audiences, content needs to be carefully adapted to be age-appropriate, culturally accurate, and ethically responsible. However, there are a number of specific challenges presented when content is multimodal, with localization applied to everything from language and tone, to gesture control and even core game mechanics. AI’s potential for efficiency here is balanced by ethical considerations for impressionable audiences.

Both of these sessions underscored a growing need for ethical AI standards in localization, ensuring inclusivity and cultural appropriateness.

3. Global Expansion: Strategies and Challenges

This year, we were treated to a number of talks that showed how important localization is in growing a business internationally, with sessions addressing monetization, payment systems, and stakeholder engagement.

• Global Monetization Strategies: Kevin O’Donnell from Global10x looked at the importance of supporting multiple currencies and customizing pricing models for local markets.Kevin explained how companies like Netflix and Spotify offer flexible payment options like regional e-wallets, or tiered pricing, to increase customer satisfaction and drive revenue growth in markets with vastly different economic backgrounds.
• Building Localization Competencies for New Markets: Subway’s Carrie Fischer highlighted how companies entering new markets benefit from cross-functional collaboration.By integrating localization early with product, engineering, and operations, they create a seamless and adaptable approach to global expansion.
• Stakeholder Education and Engagement: As localization is now on the radar of more people across the business, Junjun Cao and Karina Drosenos from Salesforce shared some practical strategies for securing stakeholder buy-in.

  By aligning expectations, demonstrating ROI, and fostering collaboration, localization teams can effectively position themselves as strategic assets within global ops.

4. Advancing the Role of Localization in the Age of AI

In a panel moderated by Phrase CEO Georg Ell, lara Altkorn from Braze and Hameed Afssari from Uber shared strategic insights on how to frame localization as a revenue-generating force, deepen customer connections, and maximize AI’s potential. Key takeaways included:

• Making Localization a Revenue Driver: Panelists underscored that localization is more than an expense; it’s a growth driver.

  By aligning localization initiatives with key metrics like customer satisfaction (CSAT) and revenue impact, they demonstrated how localization could fuel market growth. lara Altkorn shared Braze’s approach of using dashboards to track localized versus non-localized performance, highlighting Japan as a case where localized content has outpaced English-language use, showing its effectiveness in engaging regional audiences.

• Building Strong Customer Connections Through Localization: Localization helps global brands forge a deeper connection with diverse audiences, making international markets feel more accessible and personal.

  Hameed illustrated Uber’s use of tailored, region-specific content to boost engagement among riders and drivers. Despite the challenges in measuring localization’s success, the approach fosters brand loyalty in competitive markets. He acknowledged, however, that effective A/B testing in localization requires careful planning due to its complexity.

• Balancing AI with Human Expertise for Quality Localization: While AI is transforming localization, panelists agreed that human input remains crucial to maintain cultural and brand integrity. lara and Hameed both advocated a “human-in-the-loop” approach—using AI to scale and speed processes, but relying on localization experts to oversee quality and alignment with brand values.

  This balance of AI and human expertise allows organizations to efficiently expand localization without sacrificing the essential nuances that resonate with diverse, global audiences.

It’s clear that localization is moving beyond simple translation to serve as a strategic enabler of global growth and customer loyalty, and this is being recognized by more functions across international businesses.

5. Accessibility, Inclusivity, and Linguistic Diversity

A number of this year’s sessions looked at localization’s role in building digital inclusivity and increasing (and championing) accessibility – and the ROI associated with getting this right. 

• AI-Powered Accessibility: Hélène Pielmeier of CSA Research explored how AI can make digital content more accessible to people with disabilities.

  AI tools that automatically generate captions, provide real-time text-to-speech, and create audio descriptions are transforming accessibility.

  Incorporating these considerations from the outset not only improves compliance with accessibility regulations but also makes information more universally accessible, opening products and experiences up to more potential customers and users.

• Indigenous Language Digitization: Meanwhile, Roy Yokoyama of Motorola explored the technical side of things, looking at the importance of Unicode and CLDR standards in preserving endangered languages.

  For example, Unicode encoding is crucial for ensuring that unique characters, scripts, and diacritical marks are accurately rendered. Without Unicode support, these languages risk distortion, often represented by similar-looking characters from other scripts. This can easily dilute cultural accuracy and the language’s functional utility, compromising meaningful communication and digital inclusion.

  By providing a digital presence for marginalized languages, companies can help revitalize and sustain these languages.

  Craig Cornelius from Google and Tex Texin from XenCraft also discussed the wider implications of this approach, including the complexities involved in designing hardware and software to support languages with large or unique character sets.

As localization bridges linguistic gaps, these considerations are imperative in sustaining the diversity of the digital landscape, ensuring that everyone has a voice online.

6. Women in Localization and Leadership

Inclusivity was also high on the agenda for the entire conference, this year.

Several sessions looked at the role of women in localization, including a major discussion of AI’s impact on the workforce, with insights from Pia Bresnan (Uber) and Allison McDougall (G3).

• Preparing for AI-Driven Roles: In an AI-driven world, adaptability and strategic skills are essential for success.

  Emphasis was placed on mentorship, career advancement, and inclusive hiring practices as pivotal strategies to reduce gender disparities and empower women within localization.

  By fostering these initiatives, organizations can build teams that are resilient, forward-thinking, and representative.

• Encouraging Gender Diversity in AI: Many localization teams are addressing gender bias in AI by ensuring that datasets used to train LLMs mirror real-world diversity.

  This approach is vital for producing AI outputs that authentically reflect varied perspectives.

  Prioritizing inclusive data in AI development not only enhances the quality of insights but also builds AI systems that resonate more accurately across global audiences.

By fostering inclusive work environments and supporting skill development, the localization industry can pave the way for more equitable representation in AI and beyond.

7. Future-Proofing Localization Strategy in the Age of AI

Finally, a panel featuring speakers from Pinterest, Canva, and Adobe underlined the need for a forward-looking AI strategy in localization.

With the technology evolving so rapidly, professionals must be ready to adapt, and advocate for strategic, purposeful integration.

• Clear Vision and Strategic AI Integration: Localization leaders must define clear objectives and choose AI tools that enhance rather than disrupt existing workflows.

  Once again, thoughtful implementation—using AI to automate repetitive tasks while reserving nuanced, strategic work for human experts—was highlighted as the key to success.

• Build Versus Buy: To leverage AI’s full potential, localization teams must decide between building in-house solutions or partnering with specialized providers.

  This choice depends on company priorities, and many speakers encouraged leaders to weigh the benefits of maintenance and support against the risks and challenges of reinventing the wheel.

  These speakers also noted the increasing commodification and consolidation of the AI space, and the cost associations and reliances this brings with it. As with all major technology progressions, there is a balance to be struck between control and the risks of ‘building on someone else’s land’.

• Separating AI Fact from Fiction:  We were also reminded of the importance of a reality-check.

  With all of AI’s hype, critical assessment of AI’s capabilities is more important than ever. Effective stakeholder communication is crucial to maintaining realistic expectations and securing executive buy-in for AI-driven localization initiatives.

  Localization leaders were urged not to see AI as a replacement, or as a magic bullet, but as a tool for enhancement, powered by vital human inputs and skills.

  This strategic approach ensures that localization remains a valuable asset in a company’s global toolkit, enabling long-term success.

 

Conclusion

This year’s conference highlighted the localization industry’s evolution into a critical driver of global business success. From AI integration to ethical standards in accessibility, localization is proving to be more than language—it’s a comprehensive approach to building meaningful global connections.

1. Speed Matters: Optimize Site Performance for Global Users

The backbone of a frictionless experience is speed—especially for global customers who may face unstable networks or device limitations.

Alba Simon, Product Lead at Asics, highlighted the importance of performance in delivering a seamless, localized experience for e-commerce users.

“Driving a seamless experience through site speed is crucial in reducing friction, especially in ecommerce where customers expect fast, effortless transactions,” explained Alba. 

For Asics, optimizing site performance ensures customers in diverse regions experience fast load times, reducing frustration and improving the likelihood of completing purchases.

Localization plays a key role here—ensuring that your site is not just fast, but optimized for the technological capabilities and browsing behaviors of users in different parts of the world.

Alba also shared a powerful insight that businesses can take to heart: “For every second your site loads faster, conversion rates improve by an average of 17%.” This reinforces just how essential speed is in reducing friction and driving conversions.

 

2. Localization Best Practices: Shift Left for a Seamless Experience

One major takeaway from the webinar was the importance of “shifting left”—integrating localization early in the product development process.

Olga Safonova, Senior Product Manager at Workday, stressed that this early integration prevents friction by making the user experience feel more native and intuitive, no matter the language or region.

“Integrating localization earlier in product development ensures fewer obstacles when scaling globally, making the user experience more natural and seamless,”

Olga explained. This approach not only reduces the need for last-minute adjustments but also ensures that the product is culturally and linguistically adapted from the start, which is critical for a positive customer experience.

Olga emphasized the importance of involving localization experts in the early design stages, stating: 

“By involving localization experts early in the design process, we can interpret global insights and prevent misunderstandings that could frustrate users later on.”

This forward-thinking strategy can save time and resources, while improving the overall user experience.

By treating localization as a core element of product design rather than an afterthought, businesses can prevent friction before it happens, leading to smoother interactions for global users.

 

3. Cultural Adaptation: Tailor Experiences to Fit Regional Expectations

Localization goes beyond language—it’s also about understanding the cultural context of your users. 

Carolina Freire from Uber spoke about how cultural adaptation can reduce friction and elevate the user experience by making products feel more relevant and intuitive for different markets.

“Understanding the cultural nuances of your users reduces misunderstandings and allows for a more intuitive product experience,” Carolina noted.

Uber, a globally recognized brand, takes special care to tailor its app’s user experience to align with local cultural norms, preferences, and behaviors.

An excellent example from Carolina’s discussion is how cultural missteps—such as assuming universal meanings for icons—can cause friction. 

For instance, Amazon faced confusion when launching in rural India because users didn’t associate the magnifying glass icon with search but rather thought it was a ping-pong paddle! While it might seem funny in retrospect, this really highlights how important it is to understand local perceptions of design elements.

By aligning your product’s experience with local norms—whether it’s payment methods, design aesthetics, or communication styles—you can create a smoother, more engaging experience for global customers.

4. Broadening Testing: Ensure Consistency Across Regions

Testing is another critical piece of the localization puzzle. Artem Bobrovskiy from Global App Testing highlighted the need to expand testing efforts across different geographies to catch potential issues unique to specific regions before the product is launched.

Expanding testing across geographies is key to identifying friction points that are unique to specific regions,”

For a truly frictionless experience, products must be rigorously tested in real-world conditions across various countries and devices. This ensures that users in different regions encounter a consistent, high-quality experience, without unexpected bugs or usability issues.

Artem also pointed out the importance of testing in production: 

“Testing in production is crucial because it’s the only way to match the actual experience of your customers.” 

This hands-on approach helps companies identify subtle, location-specific friction points that can go unnoticed during development, ensuring a smooth experience across the globe.

5. Discovery and Delivery Adaptation: Scale Your Process for Global Success

To effectively reduce friction across different markets, both the discovery and delivery processes in product development must be adapted. 

Marcs Wilkinson, Director of Product Design at Phrase, explained that this approach ensures friction is minimized for diverse user personas. By refining these processes, companies can ensure that the localized version of their product is not only culturally relevant but also seamlessly functional.

“Adapting the discovery and delivery process not only helps in scaling globally but also ensures that friction is minimized for different user personas,” Marcs explained.

Early localization planning ensures products meet the cultural and technical needs of different markets from day one, eliminating the need for costly post-launch adjustments.

Marcs also highlighted the importance of planning for localization early: 

Localization isn’t a checkbox you tick when entering a new market. It requires planning from day one, with adaptable systems and resources in place.” 

This approach leads to a product that scales smoothly across regions, with minimal adjustments required to deliver a great experience to all users.

Conclusion: Localization as the Key to Reducing Friction in Global Products

Reducing friction in global products is about more than just solving surface-level issues—it’s about designing products that resonate with users across the world. Localization plays a critical role in this process, from early-stage product development to testing and adaptation for different markets. 

By embedding localization at every stage, businesses can reduce friction, create more intuitive experiences, and ultimately improve customer satisfaction.

Whether it’s optimizing site speed for various network conditions, integrating localization early, or tailoring the user experience to cultural expectations, each of these expert tips highlights the power of localization in delivering a frictionless global product. 

As you look to improve your product’s global reach, consider how you can implement these strategies to create smoother, more enjoyable experiences for your users—no matter where they are.

FAQs:

What is website translation?

Website translation involves converting the textual content of a website from one language into another. This process ensures that the content is accessible to users who speak different languages. Website translation often focuses on translating text such as blog posts, product descriptions, landing pages, and more​.

Do I need to translate my website?

If your business aims to reach a global audience or operates in markets where customers speak different languages, translating your website is essential. It enhances user engagement, builds trust, increases revenue potential, and gives you a competitive edge​.

What is the difference between website translation and website localization?

While website translation focuses on converting text from one language to another, website localization goes further. Localization adapts the content to fit the cultural context, including cultural nuances, legal requirements, purchasing habits, and user preferences of the target market. Localization ensures the website is culturally relevant and user-friendly for different audiences.

What does it cost to translate a website?

The cost of translating a website varies based on several factors, including the volume of content, the number of languages, and the complexity of the material. Additional costs may include localization efforts, quality assurance, and the use of a Translation Management System (TMS). Many businesses use a combination of machine translation and human translators to balance cost and quality​​.

What languages should I translate my website into?

The choice of languages depends on your target markets and business goals. Conducting market research to identify regions with high demand for your products can guide this decision. Commonly prioritized languages include Spanish, French, Chinese, Japanese, and German, among others, depending on the geographic focus and market potential​.

Which companies are already using GenAI?

Numerous companies have integrated generative AI (GenAI) solutions into their translation workflows, with varying levels of success.

For every company publicly announcing what they are doing with the tech, dozens more are actively experimenting with it, but may not yet be ready to share the results. 

It takes time to gain the necessary support internally, test it, and fully deploy an AI solution, but this isn’t stopping almost every company from trying to determine whether GPT-like applications are viable.

Let’s review a few examples of companies that have gone on the record about using ChatGPT and similar applications to produce multilingual content for their users. 

Reddit is embracing LLM-based translation

In May 2024, Reddit’s CEO shared how they are testing LLM-based translations for user-generated content housed on the platform for their French users, with a view on eventually doing so in other languages.

Reddit is betting on language AI to help drive international growth and user engagement.

AI as a tool to expand education at Khan Academy

Khan Academy, a renowned non-profit organization, uses the GPT-4-based virtual assistant they dubbed Khanmigo to deliver engaging and effective learning for students and support to teachers.

This enables them to reach a broader audience and enhance their impact.

Indeed creates multilingual jobs postings using AI

To help more people get jobs, Indeed evolved their content production pipeline from a fully human workflow to one that begins with AI. 

They’ve been using LLMs to generate multilingual content from scratch instead of translating the original copy into multiple languages, and then passing it on to human editors for quality assurance and fine-tuning.

Phrase uses AI to transform translation and localization processes

Phrase uses GenAI in its localization tech to automate complex tasks and enhance efficiency.

It improves machine translation quality, reduces human editing, and automates quality assurance, saving up to 90% on costs. 

Open AI’s latest GPT model is also integrated into Phrase’s machine translation engine as a secure, fully supported translation engine.

The ability to integrate glossaries and support tag handling ensures superior quality machine translation of content for any department across an organization.

Key considerations before translating with ChatGPT

Let’s be clear about this—testing and deploying ChatGPT in your systems will take careful planning. It will also involve getting multiple stakeholders on board, from legal, tech, IT, marketing, and product. 

Relying solely on ChatGPT to translate content straight out of the box without fine-tuning and expecting it to provide human-level translation quality is unrealistic and can even risk severely damaging brand equity.

This is due to the technology’s inherent limitations—it simply wasn’t built with translation in mind.

GPT-like applications are not a magic bullet for translating your content, so it is imperative for any business producing multilingual content for a global audience to be aware of their limitations.

Some of these limitations can be surmounted with a carefully designed process or integrating with the right technology that securely combines the power of the machine with human oversight and expertise.

• Accuracy when handling complex or specialized content: While ChatGPT excels in general translation, it can struggle with highly technical or domain-specific content.Including human oversight, with subject matter experts (e.g., professional linguists or in-house personnel) reviewing key high-visibility content is necessary to ensure a precise result. 
• Hallucinations: Language models are tuned to produce results (or say “yes” to whatever you ask of them) and have been known to produce inaccurate results or downright confabulations (frequently referred to as “hallucinations”).Training the model on high-quality data is a must to avoid this. 
• The human should remain part of the loop: AI translations, including those by ChatGPT, can miss the mark in terms of cultural nuances or idiomatic expressions.Integrating with specialist translation and localization technology that  automatically highlight a address these concerns, can help reduce this risk.Human linguistic reviews for high priority translated content can also help mitigate these issues and result in a higher fidelity output.

Data privacy and security are paramount

Before attempting to translate anything using ChatGPT, make sure you get the all-clear from your legal department about using ChatGPT or similar solutions that rely on data for training, self-improvement, and producing results. 

This should be your first step when deliberating whether to use ChatGPT for translation. 

You certainly want to prevent your employees from using the publicly available version of ChatGPT (or Google Translate) and inputting sensitive or proprietary information. 

Relying on robust data security measures, such as end-to-end encryption and secure API connections, helps safeguard critical information during translation. 

While using GPT-like applications for translation is appealing, companies must be aware of their potential and limitations and plan accordingly. 

AI technology is continually evolving, which means that deploying it will not be a single action. 

The pace of development means you will need to invest time and resources to stay on top of the latest advancements and continually test your approach.

Ensuring translation excellence when using automated translation

Regardless of whether you opt for ChatGPT for translation or not, quality should remain at the top of your mind. 

Quality requirements will differ depending on the specific purpose of the content and its type. 

Some content, such as user-generated product reviews, may not require a high degree of polish and can be processed by ChatGPT, whereas your marketing slogan will likely require multiple pairs of human eyes to get right. 

The rule of thumb is to let the purpose of the content dictate the human vs. machine vs. machine-augmented-human approach.

When considering automated translation solutions, one parameter that distinguishes GenerativeAi from machine translation (MT) is its ability to understand context, significantly improving the accuracy of the content. 

The language model can retain contextual information over longer passages, making it adept at providing coherent translations that consider the broader narrative. This is particularly important for content where meaning can shift significantly based on context. 

In addition, ChatGPT can continuously learn from new data, improving over time. Organizations can contribute to this learning process by providing translation feedback and incorporating custom training data that reflects their specific needs and language use cases.

However, remember that ChatGPT’s learning is only as good as the data it is being given. Relying on a public GPT can significantly increase the risk of low-quality or tonally inconsistent translations. 

While many GenAI providers offer a closed-loop ‘professional’ solution to combat this, you will still face issues at scale, especially if you are translating a variety of assets that require a different tonal approach. 

For example, marketing collateral may require a friendly, informal translation, while a customer help documentation may require straightforward, accurate and formal language to minimize misunderstandings. 

Making this differentiation requires a careful, standardized approach to prompt design.  This can involve additional effort and an intense Q&A process, which may negate some of the efficiency you are striving for in the first place. 

When assessing the viability of the output provided by ChatGPT, a best practice is to use a combination of industry-standard metrics such as BLEU, hLepor, or COMET that have been used for scoring machine translation (MT) engines and human evaluation. 

If all this sounds complicated, ask your localization tech provider support team or your peers to provide guidance on setting up and running an AI quality pilot project.

Beyond translation: scaling your operations with AI-powered tools

While ChatGPT offers a potentially useful translation solution that can be integrated into various systems, true excellence in translation quality and consistency requires more specialized technology.

For those seeking the pinnacle of translation excellence, the fusion of the latest OpenAI GPT model with advanced machine translation provides exceptional translation quality.

Furthermore, the integration of glossaries and automated tag handling significantly enhances accuracy and consistency.

This ensures your translations are not only precise but also aligned with your brand’s terminology, providing a seamless and professional experience across all your communications.

It’s also worth bearing in mind that AI can help with much more than just translating your content. For instance, a frequent use case for language AI is automating language quality assurance (LQA) processes. 

At Phrase, AI is at the heart of our technology and has been for several years. AI is key to how we are revolutionizing traditionally labor-intensive LQA processes. 

For example, by introducing Phrase Quality Performance Score (Phrase QPS) and Auto LQA, leveraging AI’s ability to instantly assess the quality of content that has already been translated and suggesting translators varied ways of improving it. 

Then, there is AI’s ability to orchestrate and manage translation workflows, a critical area where program managers can look for efficiencies.

AI-powered applications can streamline and automate repetitive tasks such as preparing a translation file handoff and allow your employees to focus on value-added tasks such as internal alignment and strategic planning.

Again though, this will require a more complex technology integration to ensure security and consistency, and isn’t something you can leave entirely to a single GPT-like system

Translating content with ChatGPT is just one of many potential use cases of generative AI. 

AI technology shines when used in collaboration with other cutting-edge technology,  as a tool to improve efficiencies and augment human capabilities, allowing the humans in the loop to use their expertise to validate the content and focus on designing memorable user experiences.

As you progress through the different stages toward deploying AI in real-life production scenarios, it’s important to remember that the tools will be only as good as the data you use to train them. 

Following the best practices outlined below ensures you receive the most contextually accurate and nuanced translations when using GPT-like applications.

1. Look after data quality: Use high-quality, representative data for training to ensure the model learns accurately.
2. Establish a feedback loop: Provide regular feedback on translations to help the model improve over time. A simple and lightweight means to ensure this would be to add a button that would rate the resulting translation, whereby your internal users can score the output and thus help it to improve.
3. Domain-specific training: The more detailed, domain-specific data you include, the better. 

Think of it this way. The public-facing version of ChatGPT that any user can use is pretty generalist, and you may get limited mileage out of it if you want to be specific. 

One of the best ways to improve a language model is to provide domain-specific data.

Your own data will not be extensive enough to provide consistent, high-quality results from an LLM trained on the general internet. 

Is ChatGPT the right choice for translation?

Overall, ChatGPT offers convenience for one-off or ad-hoc translations, but its limitations become evident at scale, particularly regarding consistency and quality. 

For large-scale enterprise translation needs, leveraging a more comprehensive, built-for-purpose solution is crucial. 

The right solution will combine the strengths of multiple AI engines, including ChatGPT, to deliver high-quality, consistent translations.

This will give you a more robust platform that supports extensive automation, customization, and integration, ensuring reliable and scalable localization. 

By taking a more nuanced approach and seeing ChatGPT as part of a wider translation ecosystem, you’ll significantly reduce risk while maximizing efficiency. This in turn will maintain the integrity of your brand’s voice across all languages.

We’re here to help you get ready for an AI-infused future

The rise of language AI applications represents a paradigm shift in the organization’s ability to manage multilingual communication. 

Deploying these models, provided you do so with care and work around their current limitations, can help break down language barriers within the company, and between the company and its user base, facilitating smoother interactions and ultimately improving the user experience.

Your organization’s translation needs will evolve and scale as you expand into new markets and attract new customers. 

Different stages of growth will require different translation solutions, whether human-centric or AI-augmented. 

Keep an open mind and experiment with different solutions for various content types to identify the right mix of human and machine for your budget. 

At Phrase, we understand the business of tomorrow will rely on AI to transform legacy processes and provide real-time, optimized user experiences. 

We’ve been embracing AI for many years and have developed AI-powered functionality  which is at the core of the  Phrase Localization Platform. It combines the best of both worlds—human expertise and AI’s ability to streamline processes and enhance your reach. 

We’re giving you the capabilities to translate content using AI while benefiting from industry-leading technology and quality assurance solutions while minimizing risks. 

How do you measure the real value of localization? And perhaps more importantly, how do you make sure you’re sharing that information with the right people, in a way that they understand?

It’s one question that comes up whenever we attend an event or host a webinar. And with so many different opinions and methods, it can sometimes be useful to take a step back and think about the key numbers that matter most to the business.

In this post, we’ve consulted experts from a variety of companies, and selected six essential metrics that can help you show just how effective localization can be and how it drives revenue.

 

Key Metrics for Measuring Localization Success

 

1: Turnaround Time

Let’s start with an obvious one; Turnaround time. After all, translated content is only valuable when it is out in the world, helping people!
Turnaround time is all about efficiency. With so much content being published, a quicker turnaround can be a real competitive advantage for a business, driving faster time-to-market and increased customer satisfaction.

“Delivering localized products and content on schedule is crucial for retaining customers and protecting your company’s reputation.” – Debora Cohen, Head of Localization at AppsFlyer

To measure turnaround time accurately, start simply.

For larger tasks, you can track the start and end dates of each localization task using project management tools like JIRA or Trello.

Visualizing this data with Gantt charts can help identify bottlenecks and streamline workflows. You can view this initial measurement as a research task, making sure that you don’t run into much larger issues when you begin automating tasks and driving higher volume.

This is essential if you need to scale activity, and particularly important before implementing high volume machine translations across areas like user-generated content, or customer service chatbots.  In these instances speed is often more desirable than 100% perfect translation (although of course, it’s always good to aim for both if you can).

 

2: Quality Metrics (First-time Quality and Error Rate)

 

Speaking of perfection, quality is a fundamental aspect of localization. Metrics such as first-time quality (percentage of translations that pass quality checks on the first attempt) and error rate (frequency of translation errors), help ensure high standards, but can also be a way to manage costs, by applying quality thresholds to different types of content and using this to manage workflow. 

“Quality doesn’t mean the same for everyone. Managing those expectations around quality is crucial.” – Ketty Tirrito, Localization Manager at Zendesk

It’s important to recognize that quality was often a subjective measure in the past. Language and communication preferences can be very personal, so it’s important that you approach quality in a standardized, scalable way.

Many translation providers rely on MTQE (Machine Translation Quality Estimation) scores, which group different scores into four broad categories:

 

Category	Description	Use Case
Perfect	Accurate and fluent, no significant errors	Final publication, official documents
Good	Generally accurate, minor errors	Internal communications, draft documents
Acceptable	Main idea conveyed, noticeable errors	Preliminary reviews, informal communications
Poor	Significant issues, difficult to understand	Identifying problematic translations, detailed human translation

While this can be useful, it can lack the nuance needed as you translate more content and begin automating more of your workflows. At this point, we’d be remiss not to mention our own Phrase QPS,  an AI-driven system that predicts quality scores based on the Multidimensional Quality Metrics (MQM) framework.

Capable of providing instant quality insights for both human and machine translation, Phrase QPS scores range from 0 to 100, providing greater accuracy and transparency.

Sharing this data can be simple – track errors and pass rates in your current process and collate the data. If you’re sharing this outside of the localization team, then you may not need full dashboards initially. 

Instead, use simple charts to effectively display error distribution and quality trends so that the wider business can clearly understand the effects these have on different content types. And of course, don’t forget to build in continuous feedback loops and improvement processes to ensure you are maintaining the right level of quality. 

 

3: Customer Satisfaction Score (CSAT)

 

CSAT surveys measure how satisfied customers are with localized products. High satisfaction indicates successful localization, leading to better customer retention and loyalty.

To measure CSAT, send regular surveys to users of localized content and use line graphs to track satisfaction scores over time. A good CSAT response means you can collect both quantitative and qualitative data, essential for deeper insight.

 

4: Spend by Language/Market

Tracking costs by language or market can be a big help when you want to showcase the ROI of localization, and identify areas for cost-savings or investment. 

Using KPIs like cost per word, budget adherence, and cost per revenue (Your total translation spend, divided by your total revenue) provide details that will help the business allocate resources efficiently. It will also give you suitable ammunition if you need to increase budgets to improve particular performance areas.  

“Gathering data on how much you’ve spent but also how much you’ve saved thanks to localization is essential.” – Ketty Tirrito, Localization Manager at Zendesk

 

This data can be invaluable for companies expanding into new markets, as they’ll allow more accurate forecasting of required spend over time, and will reflect wider goals over time.

On a smaller–but no less important–scale, this will help you track translation savings, which will highlight just how much value you’re getting from your translation tools, and help you discover the best places to utilize your internal localization resources.

 

5: Throughput Rate
This metric is related to your turnaround times, but allows you to dive much deeper into the efficiency of your operation.

Throughput Rate shows the amount of content passing through your system, so the higher it is, the more volume you are capable of handling. It’s related to turnaround because you’ll be using KPIs like translation output per hour to inform this number.

 

“Throughput rate provides visibility into how efficient your workflow is and also helps you understand capacity.” – Debora Cohen, Head of Localization at AppsFlyer

Again, simplicity is key to sharing this data. Use simple bar charts to visualize how many localization tasks or projects you are completing each month, and compare those over time to show how capacity is affected.

You can also go deeper by keeping track of how many of those completed projects are actually used in a given month. This will help you spot bottlenecks or create efficiencies around the business, and streamline workflows.  

 

6. Percentage of Translation Milestones Completed on Time

We all know how important it is to make sure that we’re meeting the key milestones across the translation process, and tracking and sharing this information will help you create much stronger relationships with stakeholders around the business. Again, turnaround time may appear as a KPI here, alongside more detailed numbers, like the workflow efficiency rates we mentioned previously. 

“Meeting key milestones is important to keep localization efforts on schedule.” – Ketty Tirrito, Localization Manager at Zendesk

Keep a close eye on completion dates and share them regularly. It’s also worth remembering that very few translation processes exist  in a vacuum; incorporating numbers like onboarding time here can help you understand how well you are working with third-party vendors, and ensure you aren’t risking delays. Regularly checking these numbers is a surefire way to ensure your localization projects are on track.

Sharing information with the business

While there are hundreds of possible KPIs available, the main thing to keep in mind is that you need to share the topline numbers that have the most effect on the rest of the business and its goals. 

While most of us will be adept at creating regular reports and dashboards, it’s always worth thinking about how and when to share this information. 

While a regular monthly email may be enough for some, it might not reach the whole business, so consider more creative and interactive ways as well. 

For example, displaying live dashboards can make numbers seem more relevant and exciting to teams, and showcase how new localization efforts are driving revenue in different locations. 

Hosting workshops, sharing real-life case studies, and building out training content that helps others understand the basics of measurement can also be a great way to help elevate the conversations you have with other departments, and help them see the true impact of localization.

Whichever metrics you use, sharing information this way can be a great way to make sure everyone sees the results of your hard work.

If you’d like to learn more about how Phrase is helping businesses hyperautomate the localization process, we’d love to hear from you. be sure to read about our latest updates, or get in touch to schedule a demo today.