Agentic translation

In agentic systems, AI doesn't just generate text. AI actually decides what to do next in a workflow.

Translation is the original generative task. It was the first task to shift to humans checking and fix what AI generated.

But translation workflows remained basically hard-coded. Either every new machine translation went to manual check and fix, or nothing did. Either slow and expensive, or trash quality.

In an agentic translation, AI decides when to trigger automatic post-editing, when to trigger human intervention, or when to retry with a different prompt or engine.

In practice, agentic translation that works is done by AI like ModelFront that checks and fixes AI translation, and triggers human intervention.

Working inside a TMS, it uses quality prediction to route each segment to the best path, whether automatic post‑editing or manual human post-editing, instead of hard‑coding the same path for every new segment in a file or project.

Agentic systems make sense and are already creating significant value in the real world. In translation, ModelFront is used to route billions of characters of text.

But like with AI itself, the word "agentic" is abused. It is often confused with "touchless" workflows, with zero human intervention.

In reality, AI for high-value content requires humans for training, evaluating, monitoring and re-training. And "agentic" often means triggering human intervention.

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