New Delhi, Jan. 28 -- As AI initiatives mature inside organisations, questions of governance tend to surface more prominently. Reviews increase. Approval processes formalise. Risk and compliance teams become more involved.

This shift is often interpreted as governance getting in the way. In practice, the sequence usually looks different.

Across enterprises, AI pilots often move quickly at first. Teams experiment with models, automate tasks, and demonstrate early gains. The slowdown tends to come later, when those pilots are pushed toward production and exposed to real users, real data and real risk. At that point, governance is often blamed for the friction that follows.

In practice, the opposite is usually true. What slows AI is rarel...