ARTICLE / RESOURCES · 8 MIN READ
What enterprise AI actually costs
DATE2026 / 07
AUTHORLUMACODE
Enterprise AI does not fail on model quality. It fails on the parts nobody wants to own: permissioned data, evaluation, integration and the operating model around the system once it is live.
What actually decides the outcome
The organisations that ship treat the programme as infrastructure work. They name the metric before the build, instrument the baseline, and give the system an owner who is on call for it.
- —A named metric your board already tracks
- —A written governance framework, two pages is enough
- —An evaluation set that predates the first deployment
- —One owner accountable for the system in production
If you cannot state the pre-deployment number, you cannot defend the post-deployment one.
Where to start
Pick the smallest system that proves the value, ship it into production, and let the second one inherit everything the first one had to build.
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