“Most of the time, AI is touching confidential data or business-critical data,” Aerni says. “Then the thinking about the architecture and what the workload should be public vs. private, or even on-prem, is becoming a true question.”
The public cloud still provides maximum scalability for AI projects, and in recent years, CIOs have been persuaded by the number of extra capabilities available there, he says.
“In some of the conversations I had with CIOs, let’s say five years ago, they were mentioning, ‘There are so many features, so many tools,’” Aerni adds. “Now when I’m having the same conversation, they say, ‘Actually, I’m not using those tools that much now.’ They are all looking for stability and predictability.”