Verticalisation refers to AI applications that are trained for specific industries and use cases. “If you’re in finance, as an example, you’re training these models to understand credit risk, how that process works, claims adjustment, things like that,” he says. “That’s what we see with verticalisation.”
Enterprise artificial intelligence (AI) has come a long way. Just three years ago, a project would typically begin with a blank sheet and a prototype pilot. Those days have changed. Now, boards want to see returns on investments (ROI) and C-suites want proof. To David Irecki, chief technology officer at integration platform Boomi, the shift has fundamentally changed the conversation.
“What we’re seeing now is there’s a lot of pressure from the board and C-suites and organisations to show value and ROI, and one of those things is verticalisation,” says Irecki.
