What if the biggest barrier to Bible translation isn't time or money—but capturing the right data? In this episode of the Global Missional AI Podcast, we explore how two organizations are revolutionizing Bible translation for the world's lowest-resourced languages.Jacob Bullock from SIL Global and Daniel Wilson from XRi Global share their groundbreaking approach to collecting and optimizing language data. Daniel reveals a stunning calculation: Kenya's 300,000 teachers could generate a trillion tokens of Swahili—enough to train a large language model—in just two months. The challenge isn't data scarcity; it's strategic data capture.We discuss the next frontier in AI-assisted ministry: moving from early adoption to scalability. Jacob explains how they're helping Bible translators find their identity as "skilled craftsmen" who use AI as a tool rather than viewing it as a replacement. Daniel shares practical examples of "AI-first" workflow, including how AI agents completed hours of research while he cleaned his garage.Key topics include:Why "low-resource languages" is almost a scandal when data is abundant but uncapturedThe science of optimizing "intelligence per sentence" in data collectionHow to develop new muscle memory for AI-powered knowledge workThe identity question: "Who am I in the world of AI?"Accelerating not just Bible translation but Scripture engagement across all resource levelsWhether you're in ministry, missions, or simply curious about AI's role in reaching unreached people groups, this conversation offers practical insights on bridging the gap between technological possibility and kingdom impact.