India, Sept. 29 -- There was a time when adding AI to a technology roadmap largely meant identifying a few use cases, running pilots and figuring out where the technology could improve productivity.

That phase is rapidly giving way to a harder one.

As AI moves deeper into products and engineering organisations, technology leaders are confronting questions that go well beyond which model to use.

What happens when AI starts writing a meaningful share of production code? Who verifies it? How should engineering teams change when individual developers can produce substantially more? What happens to infrastructure costs when an AI feature moves from a pilot to millions of users?

At the product layer, another shift is underway. Search boxes ...