AI transformation

AI transformation changes how an organization chooses, builds, and operates its systems. Our coverage connects executive decisions with the infrastructure and engineering work behind them: private model platforms, AI factories, software delivery, and the people responsible for making the transition useful.

The builder’s advantage
The FDEs are coming. Sam Sweilem on agentic engineering, private AI, and the cost of waiting for consensus.
Before the rewrite, prove the behavior
AI can accelerate the construction of a replacement. The difficult modernization decision is knowing which obligations the new system must preserve—and when it can take over.
The cost of an AI job that actually gets done
A lower token bill can hide a more expensive operation. Enterprise AI economics starts with accepted work, including the time and infrastructure needed to finish it.
Jensen Huang’s AI factory thesis meets the enterprise
NVIDIA’s infrastructure argument is becoming an operating agenda: define the work, engineer the whole system, and measure useful output.
Andrej Karpathy and the new value of engineering judgment
As coding agents take on more implementation, the scarce skill shifts toward context, verification, and understanding what the software should do.
Nagendra Bandaru and Wipro’s AI-Native Contact Center Playbook
How Wipro Healthcare Process Solutions paired NVIDIA’s AI stack with a phased operating model—and the performance measures CIOs should examine before scaling.