LinkedIn·Monday, 17 August 2026·8d ago

You've shipped AI and things are in production. But if someone asked you right now what's actually running, who owns it and whether it's…

Collibra

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You've shipped AI and things are in production. But if someone asked you right now what's actually running, who owns it and whether it's still behaving the way it was six months ago — could you answer that? Most AI leaders we talk to can't. Not because they haven't thought about it, but because the portfolio grew faster than the infrastructure to see it. And that gap has a way of showing up at the worst moments. A data feed changes in the background, the models depending on it keep running and weeks later someone notices the outputs look off. This is what scaling AI looks like right now for most organizations, and it's a big part of why Gartner predicts 6 in 10 enterprises will fail to realize AI investment value by 2027. We wrote the guide for commanding AI at scale, including a 28-point readiness checklist to benchmark where you stand today. Link in comments. 👇

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