Most AI investments don’t underperform because the models are bad. They underperform because the infrastructure to support them was never built.
Many organizations have spent years funding AI, but find the models still aren’t working the way anyone hoped.
The pattern is familiar. Budgets were approved. Talented teams were hired. Initiatives launched. A few made it to production, and those are now quietly degrading. No one has flagged it yet.
The models weren’t the problem. The systems around them were.
That’s the gap MLOps closes.
