Balancing automation, accuracy, and authenticity: AI in localization
How can global brands use AI in localization without losing accuracy, cultural nuance, and brand integrity? In this podcast, host Bill Swallow and guest Steve Maule explore the opportunities, risks, and evolving roles that AI brings to the localization process.
The most common workflow shift in translation is to start with AI output, then have a human being review some or all of that output. It’s rare that enterprise-level companies want a fully human translation. However, one of the concerns that a lot of enterprises have about using AI is security and confidentiality. We have some customers where it’s written in our contract that we must not use AI as part of the translation process. Now, that could be for specific content types only, but they don’t want to risk personal data being leaked. In general, though, the default service now for what I’d call regular common translation is post editing or human review of AI content. The biggest change is that’s really become the norm.
—Steve Maule, VP of Global Sales at Acclaro
