I spoke with a CISO recently who viewed shadow AI primarily as something to lock down. That instinct makes sense, but it might be missing the bigger picture.
In a few CIO roundtables I’ve been part of around Boston, the same pattern keeps coming up: shadow AI is growing faster than IT can keep up. The typical responses tend to fall into two camps,either clamp down hard or ignore it altogether.
But there’s a more useful way to look at it: this isn’t just a security problem, it’s a visibility problem. People are adopting these tools because they’re useful. If the approved stack doesn’t meet their needs, they’ll go elsewhere, and that usage becomes invisible.
The organizations handling this better aren’t starting with restrictions. They’re starting with visibility, understanding what’s actually being used, then deciding what to govern, what to formally support, and what to phase out or replace.
Has anyone here found a way to move beyond the “block vs. allow” approach to shadow AI? What’s actually working in practice?