Demo to production, the gapFrom Community editorial
What happened: Across 40+ enterprise AI implementations we tracked this cycle, the pattern repeats: a working demo ships in weeks, then the project stalls for months before (or instead of) reaching production. The blocker is almost never model quality.
Why it matters: Teams keep optimizing the thing that already works (the model) while ignoring the things that actually kill projects — data access approvals, unclear ownership after the pilot team moves on, and no plan for what happens when the model is wrong.
40+Implementations tracked this cycle
Originally published on ayraix.com, practical AI for enterprise builders.
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