AI amplifies what’s already there. And for most teams, that’s the problem. Last week I co-hosted Session 1 of GALA Academy’s three-part course on AI for the language industry. L’Meese Greaney is up next (Sales, May 12). Erik Vogt closes it out (Growth, May 19). They’ll both be excellent.

What is Multilingual AI? Multilingual AI is a capability stack that lets software handle language across regions. It goes well beyond just translating and includes reasoning about meaning, tone, and correctness across locales. It typically shows up as: Text: search, chat, summarization, writing, support Speech: transcription, speech-to-text and speech-to-speech translation, dubbing Multimodal: voice + text + UI, with market-specific expectations baked in Translation is part of it, but...

What’s going on with jobs in the language industry? Some roles are fading. Some are mutating in real time. And a few new ones are popping up that basically tell us where this whole thing is (probably) heading. Their titles don’t always say “AI” or “agents”. But the job descriptions do.

Last week, I spent two afternoons glued to my screen attending Loc Tech Live 2026, a virtual conference that brought together 340 localization professionals to discuss the messy, technical "how" of localization. The event went deep: architecture diagrams, code demos, and the real infrastructure behind localization at scale. Not my natural habitat, to be honest. But given how localization is evolving, it's a world everyone needs to understand, at least to some extent.

We all need to be good at marketing, even if we don't work in marketing. And it's not just about brands or products. In the language industry, as everywhere else, we need to know how to market our function (why we exist), our team (who they are and what they do), and ourselves (why we remain relevant).

There is one thing we don't talk about nearly enough these days: AI. Or, ehm, the cost of multilingual AI when using AI for language-related tasks.