- "SMB에게도 AI가 필수··· IT 예산 할당 증가" IDC
- Why 1Password's new location feature is so handy - and how to try it for free
- HPE cuts 2,500 jobs, expects Juniper buy to close year-end ’25, faces tariff issues
- The Must-Have Skill Every Network Engineer Needs
- The free iPhone 16e deal at Visible is still available. Here's how to claim yours
CIOs’ lack of success metrics dooms many AI projects

“People think that AI is in some way magic, that it’s going to be a point that’s going to solve all the problems in one go,” he adds. “There is a reasonably significant amount of work in dealing with AI, depending on the use case. It isn’t just a case of picking something up off the shelf and running it.”
In some cases, a failed AI experiment may be educational and point organizations to better projects, Curtis says. But many organizations, after seeing a high majority of their AI POCs fail, may stop experimenting.
“A lot of financial services companies that I work with don’t have a risk culture,” he says. “If something fails and they spent millions of dollars on it, they’re likely not to do it again.”