A lot of AI projects look great in a pilot. Very few make it to production. At NVIDIA GTC, I sat down with Glenn Dekhayser from Equinix to understand why. And the answer is not what most people expect. It is not just about models. It is about everything around them. We talked about why so much enterprise data is still unusable for AI.

- Siloed systems

- Lack of structure

- No clear path from data to deployment

And then there is infrastructure. Because scaling AI is not just about training a model once. It is about running it reliably, securely, and close to where the data lives. That is where most projects break. One idea that stood out. Thinking of the data center as an “AI factory.” Not just storage. Not just compute. But a system designed to continuously turn data into outcomes. And that changes how enterprises need to plan.

From day one. If you are serious about AI, this is the shift. From experiments to infrastructure.

More conversations coming from GTC.

#data #ai #equinix #NVIDIAGTC #theravitshow