There is a recurring conversation happening in boardrooms right now that usually goes like this:
—We’re using AI translation now. It works great.
—How is quality measured?
—Well… we ran a few tests upfront. They looked good.
This is a classic symptom of what was identified at SlatorCon as the "Prototype Phase."
It is the "this is easy" stage. LLMs are highly effective at producing fluent first drafts, leading many engineering or marketing teams to believe the job is done. But deploying AI without systematic evaluation is like flying blind at scale.
The "Magic Box" Reality Check
Treating AI as a magic box (content in, translation out, fingers crossed) works until you hit the "Deployment Stage." This is where complexity arises. AI doesn't intuitively understand tone guidelines. It doesn't know when "professional" implies "warm" versus "authoritative."
Without the right infrastructure, the risks are real:
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Brand Erosion: One off-brand campaign can undo months of positioning work.
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Liability: Hallucinations aren't just factual errors; in regulated industries, they are non-existent contract terms or false product specs.
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Invisible Errors: The most dangerous mistakes are the ones that look fluent but are factually wrong. These are the ones harder to detect, by the way.
Moving from Experimentation to Enterprise Scale
The gap isn't the technology; it’s the quality infrastructure around it.
To graduate from the "this is complicated" stage to the "Enterprise Stage," organizations need a systematic safety net. This is where Agentic Evaluators come in. They are autonomous systems that assess what human reviewers can't scale: accuracy, hallucination detection or legal terminology precision, amongst many other metrics.
But technology alone isn't enough. Scaling requires a Process Partner: experts who can integrate state-of-the-art tech with deep process expertise.
At Kobalt, we help teams bridge the gap between "it looks good" and "it works at scale." We provide the metrics, control, and localization expertise needed to turn AI from a risky experiment into a reliable business asset.
Are you planning to tighten your AI translation quality strategy for 2026?
Let’s move beyond the magic box.
