Ingram Micro sits down with Moses and Nick from TGIX to explore why so many AI initiatives stall out in proof-of-concept and never reach production. They break down TGIX's holistic approach to AI transformation — from infrastructure and data pipelines to security — and share real examples of helping public sector organizations modernize for the AI era.Key Takeaways🧩 Stitching it all together — Most AWS partners specialize in one lane (migration, data, security). TGIX's differentiator is a holistic view across infrastructure, data pipelines, and applications so nothing gets left disconnected.🏗️ Foundation before flash — Organizations chasing the newest AI models without solid technical foundations rarely scale past proof-of-concept; the ones that succeed invest in infrastructure first.🚗 Old architecture, new workloads — Cloud environments built pre-AI weren't designed for it (the "two-lane road" / "EV on horse-and-carriage roads" problem), so refactoring is often unavoidable, not optional.🎯 Work backwards from mission outcomes — TGIX starts every engagement by understanding the client's business/mission drivers, then identifies infrastructure and data gaps before recommending any AI buildout.Timeline00:00 – Welcome & introductions00:29 – What problems is TGIX solving?01:19 – Why AI requires a full technology overhaul02:13 – TGIX's nonprofit + GenAI competency combo03:33 – Do cloud environments need refactoring for AI?05:15 – What an AI transformation process looks like07:19 – Balancing speed vs. doing it right08:26 – Why you can't just "layer" AI onto old systems09:56 – Real transformation example: Medicare/Medicaid fraud detection11:47 – Staying ahead of AI instead of playing catch-up