The engineering system surrounding an AI model increasingly determines whether its intelligence can be delivered reliably, economically, and at scale
The next competitive advantage in enterprise AI has less to do with which model you choose than with what you build around it
That's an important shift. For the past several years, much of the AI conversation has centered on model capability: bigger models, better reasoning, larger context windows, higher benchmark scores. Those advances have been extraordinary. But as AI moves from experimentation to production, the question facing enterprise leaders has changed—it's no longer, "what can the model do?"—it's now, "Can we deliver that intelligence reliably, economically, and at scale?"
