AI-assisted engineering teams: 63% say their scope grew in the past year. 45% are working longer hours. Both numbers point to time spent maintaining code that's already shipped, not time spent writing it.

AI speeds up how fast software ships, not who's watching what shipped afterward. ActiveState's latest breakdown names four places that gap costs a business: engineering capacity, roadmap predictability, platform team workload, and ownership.

None of those four show up as a line item until they're already late. A dependency added in seconds can sit in production for years before anyone checks on it again.

94% of CISOs say their organization's AI appetite grew this year. More than half also think adoption is already outpacing them. Both are true at the same company, at the same time.

The fix: govern what comes in before it becomes next quarter's maintenance backlog, not slow AI down trying to catch up after the fact. Full breakdown in the reply below. Where does this show up first on your team: the roadmap, the backlog, or a Slack thread nobody's resolved yet?