The models are already good enough. The failures almost never trace back to the model.
MIT put a number on it in 2025: 95% of enterprise gen-AI pilots show no measurable return. The root cause isn’t weak technology — it’s that these systems don’t learn, don’t accumulate, and don’t adapt to how the organization actually works.
The tools arrived. The organization didn’t change.
Most “AI transformations” amount to handing out tools. Someone drafts copy with them, someone answers questions, someone builds spreadsheets. Work gets a little faster — but the organization itself doesn’t change: same processes, same decisions.
That’s the gap between using AI and becoming an AI-native business. The first changes nothing. The second is an order-of-magnitude difference.
The last mile only closes with someone on the ground
From pilot to production, from tool to organization — that mile can’t be bought and can’t be installed. It takes an engineer inside the business, seeing how decisions actually flow, where value leaks, and where it compounds — then building AI into the grain of the operation, where it takes root and keeps growing.
That is exactly why Forward Deployed Engineering exists.