The question nobody’s asking — and why the answer determines whether your tools actually work in the field. Everyone’s getting the same pitch: AI makes building software so easy, your team can build exactly what you need without a platform. That’s not wrong. It’s just missing the most important part of the conversation. The code is the easy problem. The hard problem is what you’re building on. Field apps require a specific foundation — offline sync, GIS capabilities, validation logic, consistent data storage — that takes years to get right and costs more to rebuild than most teams realize. And if you’re thinking about AI long-term, that foundation is also what determines whether your field data is actually useful as AI input, or just another pile of inconsistently structured records. This session makes the infrastructure case that’s mostly absent from the current AI conversation in field operations. You’ll come away with: A framework for evaluating what foundation a field app actually needs A clear picture of what it would cost to build that foundation from scratch, versus building on top of it. An understanding of how data consistency changes what AI can do with your field data downstream
