Productivity levels in the language service provider industry have stagnated in recent years. Over the last decade, we’ve seen advances such as post-editing, predictive typing, and the latest LLMs combined with neural machine translation. However, these tools often require time-consuming, segment-based processing. We’ve also introduced probability scores so that language specialists don’t have to verify everything manually. But is this the path toward significant productivity gains? By leveraging AI agents, you can drastically reduce the time needed from translators and project managers. These AI agents can be programmed to handle specific tasks at both the beginning and the end of a project. So, how can you enable AI agents in your multilingual content creation process?
What does an AI agent do?
Many of you are familiar with AI agents embedded in products designed to enhance content creation. For instance, think about the premium version of the YOAST plugin, which helps optimize meta titles and descriptions in WordPress using AI, or the functionality in CAT tools that assist with searching for word explanations or verifying their validity. While these built-in AI agents are useful, do they really speed up the overall process? In reality, the difference is often marginal.
With tools like ChatGPT, you can create agents specifically designed to perform certain tasks. The more targeted these tasks are, the better the results. Successful use cases of AI agents in multilingual content creation can be seen at companies like Klarna. In previous years, a company like Klarna might have turned to solutions like Unbabel, which helps organizations with real-time translations for customer support queries. When set up correctly, AI agents can reduce human interactions.
Implementing AI agents in the multilingual content creation process can save significant time—time that would normally be spent by local language specialists reviewing the entire output. Of course, for critical content, a specialist should always review the results. However, AI agents can produce in a lot of cases more precise outputs than traditional translations, ultimately saving language specialists time.
What role can AI play in content creation?
AI agents can be integrated at both the beginning and end of the content creation process. At the start, they can prepare, create, validate, enhance, and adjust content before it reaches the language specialist. Using data (which may be in different languages) and instructions, AI agents can generate specific outputs tailored to a target audience—far more efficiently than traditional transcreation.
At the end of the process, AI agents can verify that the content aligns with style guides, instructions being applied, terminology usage, and maintains overall consistency. This process isn’t limited to an AI console. Think outside the box: consider using an API query to place results or comparisons in diferent formats on Google Drive or SharePoint.
A common question when using AI agents is whether to provide them with segment-based output, paragraphs, or even full pages of content based on instructions. In the language industry, we’re often bound to segment-based workflows, which is our productivity pitfall. Looking at this movement, we can still use segment-based data, however the traditional methods of translation and post-editing will fade away, giving way to new more efficient approaches that boost productivity.
How effective can it be?
AI agents can be embedded at various points in the process, placing them in the beginning or the end is the most challenging step. The quality of the output can vary significantly if instructions are too vague or datasets are not applied correctly. That said, the upside is substantial once these agents are properly implemented.
We’re only at the beginning of the AI agent revolution. Industry leaders like Bill Gates and Sam Altman have predicted that AI agents will assist us in many day-to-day tasks. By setting up the right infrastructure now, like Klarna has, you’ll be ready to ride the wave of AI. When major updates are made to large language models (LLMs), you’ll be able to quickly update your AI agent to improve its performance.
Getting Ahead of the Curve
At Linguatech, we are using AI agents to help us create, validate, enhance, and perform many other tasks to boost both our productivity and the quality of our output. We focus on enabling human creativity and eliminating repetitive tasks. This applies not just to content creation, but to strategic thinking as well. Across our five subsidiaries of translation agencies, we have a wealth of local specialists who can focus on delivering quality output, thanks to the assistance of AI agents.
We’ve been using AI agents in various ways to support our internal needs and to assist clients who are looking for more affordable, targeted content that aligns with their strategies. With the rapid rise of AI, we expect to continuously increase content output while maintaining the same budget.
