Making AI trustworthy does not constrain growth
Enterprises need transparency and controls from model providers before allowing access to data and workflows
PACING frontier development may give AI model companies more time to improve safety, alignment and interpretability. But none of that, by itself, makes a chief executive more willing to connect an agent to payroll, customer records or production scheduling.
Even as diligent testing and alignment increase confidence in an AI model, enterprises still need to know what they are accepting when they give it access to their data, workflows and decision rights.
In my conversations with large enterprises across Asia, the real constraint has moved further down the stack, from frontier capability to deployability. And it sits inside the companies putting these systems to work.
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