When AI Starts Acting
Agentic AI isn’t enterprise ready yet. Here’s what CEOs should do now to prepare—without hype or theory.
Agentic AI is already being used inside companies, but almost always with strict limits, humans in the loop, and heavy logging.
OpenClaw proves autonomous agents work in practice, while also exposing why ungoverned autonomy fails fast.
The winners are defining delegation rules, controls, and protocols before scaling autonomy.
Here’s the truth most CEOs don’t hear clearly enough:
Agentic AI is already inside companies, just not where marketing decks say it is.
Not replacing people.
Not running wild.
But quietly doing bounded work under supervision.
And when those bounds aren’t clear, things break fast.
OpenClaw: Useful Signal, Unsafe Default
The recent attention around OpenClaw isn’t because it’s enterprise-ready.
It’s because it shows something uncomfortable and real:
Software can now remember, decide, and act without waiting for you.
That’s why Tim O’Neill’s piece on OpenClaw matters, not for the hype, but for the warning it implicitly carries about what happens when autonomy arrives before governance.
In practice, what teams discovered:
Agents complete work faster than expected
Errors happen faster too
Security and legal get involved immediately
That’s not failure.
That’s the cost of learning where delegation breaks.
What Enterprises Are Actually Doing Today
Forget “fully autonomous.”
That’s not how this is being deployed in the real world.
1. Autonomy is tightly scoped
Real deployments look like:
