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From Hype to Reality: What We’ve Learned About AI


10 min read

Written by


Argos Multilingual

Published on

02 Jul 2024

Artificial Intelligence (AI) is bringing new ideas and technology to the localization industry, offering fresh opportunities and unique challenges. Our latest research, Beyond the Hype: State of AI in Localization in 2024, sheds light on how AI is currently utilized, the challenges faced, and the successes achieved by localization teams. 

This latest installment of our blog series provides a snapshot of real-world experiences from the report, as well as examining AI maturity, practical applications, and strategic approaches to integration. While we can’t predict exactly where this technology will lead, we can identify emerging pitfalls, explore how AI is being used today, and offer guidance to help you on your journey.

Understanding AI Maturity in Localization

It helps to understand where you are before you can figure out where you’re going.

AI maturity in localization refers to a team’s level of awareness and readiness to integrate AI capabilities into their workflows. It’s a measure of how well a team understands AI’s potential and how prepared they are to leverage it for localization processes. As teams progress through different stages of AI maturity, they become more adept at incorporating AI.

Argos AI Maturity Model (AIMM)

To help localization teams assess their progress in adopting AI, Argos Multilingual developed our AI Maturity Model. This model provides a structured pathway for teams, guiding them from basic awareness of AI to full integration. By understanding where they stand on this maturity curve, teams can identify the next steps they need to take to advance their AI capabilities. 

By progressing through these stages, localization teams can not only systematically enhance their AI capabilities but also start using this new technology in ways that best support their processes, workflows, and operating models.

Real-World Challenges in AI Adoption

While the potential gains from using AI in localization are great, the path to implementation isn’t simple. Understanding and addressing these hurdles is the only way for localization teams to leverage AI effectively. Here are some of the most common issues we’re seeing right now.

Limited Resources and Expertise

Many localization teams lack the necessary resources and expertise to implement AI solutions effectively. Finding personnel with the technical knowledge required to manage AI technologies can be difficult, leading to slower adoption rates and suboptimal use of AI tools. Investing in training and recruiting new talent can be time-consuming and costly.

Integration with Existing Processes

Integrating AI with established localization workflows is often challenging. Long-standing processes can be disrupted by the introduction of new AI-driven tools. A phased approach, where AI is gradually integrated and continuously monitored, helps ensure that AI enhances rather than hinders productivity.

Accuracy and Cultural Relevance

Maintaining high standards of accuracy and cultural relevance in AI-generated content is a persistent challenge. While AI tools are improving, they still struggle with nuances and context that humans handle well. Ongoing human oversight and robust quality assurance processes are necessary to ensure AI outputs meet the required standards.

Regulatory and Compliance Issues

Ensuring regulatory compliance with established rules can be challenging, and even more so with emerging technologies like AI. Regular audits and staying updated on legal requirements are essential to avoid legal issues.

How Companies Are Using AI Today

Artificial Intelligence is poised to become a key component in localization. However, its long-term role in language services is still taking shape. While many companies are actively experimenting with AI, its current applications in localization are still quite limited.

Our Beyond the Hype: State of AI in Localization in 2024 report highlights how some companies are integrating AI into their workflows and processes right now. Here’s an overview of some of the most common ways AI is being used today.

Quality Evaluation and MT Workflows

AI tools are improving quality evaluation by predicting translation quality and integrating with machine translation (MT) workflows. These tools assess translations for accuracy and fluency, allowing localization teams to catch potential issues early and reduce manual review efforts. AI-powered quality evaluation helps streamline workflows, ensuring standards are maintained while accelerating the translation process. 

Translation Memory Cleanup

Managing translation memories (TMs) is crucial for translation consistency and accuracy. AI automates the cleanup process by identifying and resolving inconsistencies, duplicates, and outdated entries. Before AI, TM cleanup was done manually, making it time consuming and cost prohibitive. Now, with automation saving significant time and cost, TM management can become a proactive strategic advantage. 

Prompt Engineering

AI enhances the process of crafting and refining prompts to ensure translations are more accurate and contextually appropriate. Effective prompt engineering is particularly valuable for maintaining brand voice and cultural nuances, ensuring that the final content resonates with target audiences. By optimizing the quality of prompts, localization teams can regularly produce high-quality translations.

Content Creation

Some language service providers are using AI to make content creation and workflow automation easier. AI-driven content creation tools assist in generating initial drafts for various types of content, such as product descriptions and marketing materials, which are then refined by human translators. Other companies, such as Canva, are using AI to improve the localization coverage of their landing pages, for example.

Workflow Automation

In project management, workflow automation powered by AI helps automate task assignments, track deadlines, and optimize resource allocation, streamlining operations and reducing administrative overhead. In some platforms, AI also monitors progress in real-time, providing alerts for any potential delays and adjusting schedules dynamically to maintain deadlines. 

Customer Support

AI is also transforming customer support by deploying chatbots and virtual assistants capable of handling inquiries in multiple languages. This improves response times and ensures consistent and accurate customer interactions. 

As these examples show, AI is proving to have many practical benefits, especially in improving efficiency, accuracy, and quality. 

How to Start Approaching AI in Localization

Integrating AI into localization workflows is not a question of if or when, but how. Our AI report offers valuable insights into starting this journey. 

Here are a few ideas from our report to consider as you begin to approach AI – for the full details, be sure to download your copy.

  • Identify Low-Hanging Fruit: Determine where AI can provide the most immediate and substantial benefits.
  • Build a Roadmap: Consider a phased approach that balances immediate needs with long-term goals.
  • Collaborate Across Departments: Successfully integrating AI requires working across departments to address potential challenges and align with organizational goals.
  • Focus on Continuous Learning: AI technology is constantly evolving, and staying updated with the latest advancements is essential.
  • Embrace Experimentation: Adopt a mindset of trial and error for tools and approaches to find what works best for your needs. 

Remember, AI has the potential to automate many tasks, which enables teams to focus on more customer-facing, strategic, or creative work.

Getting Ready for an AI-Powered Future

While AI may not fundamentally change the day-to-day reality for localization teams yet, it is clear that AI will play an increasingly prominent role in the future. As it matures, AI could potentially automate many tedious and repetitive tasks, freeing up staff to focus on more strategic and creative aspects of localization. This is why it’s important to take a proactive approach to AI and prepare for the future that is rapidly approaching.

For more comprehensive insights and strategies, download the Beyond the Hype: State of AI in Localization in 2024, which offers valuable insights about navigating the complexities of AI in localization.

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