One pattern we see a lot when working with clients is that AI adoption is labelled as a “technology project”, so everyone assumes it has to start and be led by IT.
In practice, that’s rarely how it works.
The strongest AI initiatives usually begin as business problems in finance, ops, HR, or sales. But for any technology project to be successful, IT and the CTO still need to be involved. The challenge is how you bring them in without slowing things down or losing all losing momentum completely.
In my experience, CTOs tend to fall into one of two camps:
- Very excited about AI and keen to explore it.
- More cautious, wanting control, governance, and clarity before anything moves forward.
Both are reasonable positions.
If they’re excited by the technology, the opportunity is helping them translate that excitement into real business use cases. CTOs don’t always live inside finance or ops workflows, so pairing their technical curiosity with real process context is where momentum comes from.
If they’re more cautious or want to build everything themselves, reassurance matters. It helps to be clear that they’re not losing control. With Brim, they still get audit logs, traceability, visibility into how agents behave, and the ability to explore models and logic. What they don’t have to manage is the infrastructure overhead, scaling complexity, or ongoing maintenance.
That balance often lands well. They keep the parts of the job they enjoy and are responsible for, while a lot of operational burden is taken off their plate.
Whichever camp they’re in, AI adoption works best when IT is involved as a partner, not a gatekeeper and a blocker.
Would love to hear whether this matches others’ experiences, and any approaches that have worked well (or not) in real client work?