In the localization industry right now, there is a heated debate happening. On one side, agencies are promising clients “half the cost in half the time” thanks to Large Language Models (LLMs). On the other side, veteran translators are sounding the alarm, claiming that “common sense” is being replaced by unrealistic spreadsheets.<\/p>\n
A recent industry discussion highlighted a growing frustration: If LLMs are so powerful, why does the “review” process now take three times longer than it used to?<\/p>\n
At VDA Translations, we believe both sides are right, but only because most people are using the technology the wrong way.<\/p>\n
The current trend in the market is to treat AI like a “magic button.” The workflow looks like this:<\/p>\n
The Reality:<\/strong> LLMs are prone to “hallucinations,” terminology inconsistencies, and a lack of cultural context. When a reviewer is handed a document that looks correct but is riddled with invisible errors, their mental workload skyrockets.<\/p>\n Instead of a one-hour polish, they spend three hours rebuilding the text. Suddenly, the “cheap” AI translation costs more in human hours and management overhead than the traditional process ever did.<\/p>\n <\/p>\n This approach focuses on front-loaded preparation to ensure the AI translates with full context:<\/p>\n The Outcome:<\/strong> Highly consistent copy, quick turnaround, and reliable brand assets.<\/p>\n This workflow treats AI as a zero-cost shortcut, leading to major correction overhead:<\/p>\n The Outcome:<\/strong> Skyrocketing hourly costs, high stress, and critical errors reaching your live copy.<\/p>\n The problem isn’t that AI doesn’t work. The problem is that many agencies are skipping the most important step: The Architecture<\/strong>.<\/p>\n When an LLM disregards terminology or flips the meaning of a sentence, it’s usually because it wasn’t given the right context. Most agencies provide a “naked prompt” to a generic model. This is like asking a genius who has never seen your brand to write your marketing copy in 10 seconds. They will guess, and they will often be wrong.<\/p>\n \n “LLMs work as advertised when operated correctly.” This means:<\/p>\n At VDA Translations, we see the shift in the landscape not as a reason to cut rates, but as a reason to increase expertise.<\/p>\n We don’t believe in the “Press of a Button” model. Instead, we treat the AI as a high-performance engine that requires a skilled driver. Here is how we bridge the gap between “cheap” AI and “expensive” errors:<\/p>\n If a provider promises you “perfect” results for a fraction of the price by simply hitting a button, be careful. You might end up paying for that “saving” with your brand’s reputation when the errors inevitably surface.<\/p>\n The future of localization isn’t about replacing translators with machines; it’s about replacing outdated workflows with smart, engineered solutions.<\/p>\n Good translation still costs money, but with the right technical approach, that money buys you more consistency, more speed, and more peace of mind than ever before.<\/p>\n Let’s discuss how a specialized Dutch and Spanish expert can help you build a process that actually works.<\/p>\nWorkflows Compared: Quality vs. Error Cycles<\/h2>\n
The Cycle of Quality (Recommended)<\/h3>\n
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\nThe Cycle of Error (The “Magic Button” Trap)<\/h3>\n
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Why AI “Fails” (And Why It’s Actually a Human Error)<\/h2>\n
\n , Tobias Ernst, Industry Forum<\/cite>\n<\/p><\/blockquote>\n\n
The VDA Approach: From “Post-Editing” to “Prompt Engineering”<\/h2>\n
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The Bottom Line<\/h2>\n
\nTired of “good enough” AI translations?<\/h3>\n