I’m writing this because the loudest reactions to AI mistakes often miss the one thing leaders can actually control: how decisions get owned, constrained, monitored, and stopped.
If you’ve ever watched a story like this unfold, you’ll recognise the pattern:
Here’s the thing. Most “AI disasters” are not magic. They are process failures with an AI-shaped trigger.
Glen McCracken captured the core problem better than most:
"Every time I hear someone say “AI went rogue” they reveal something important. They have no idea what they are talking about. AI does not wake up at 3am, creep around your servers, and arbitrarily decide to send an email to all suppliers... Most AI “failures” share the same root cause: no one owned the decision."
That line, “no one owned the decision”, is the leadership takeaway.
Not “ban the tool”.
Not “blame the user”.
Not “panic about the future”.
Agentic workflows are systems where an AI can plan and take actions across tools, not only answer questions. That is powerful, and it is also where risk lives.
Most failures look boring in hindsight:
David Biggs put it bluntly, and I agree with the spirit of it:
"Any advanced program has gaping holes and tons of missing parameters/guardrails, not to mention architecture often built on limited imagination input. This is both because of the well-documented commercial marketing push to \"just get it out\" before it's ready, as well as the fact that any program with a million lines of code will simply have logic and parameter gaps. That's what beta testing is even for."
If you lead a function, a product, or a business unit, this should change your posture from “Can we trust AI?” to “What must be true for this workflow to be safe?”
Teams often talk about agents as if they are junior staff. That is a useful mental model for productivity, and a dangerous one for governance.
Because infrastructure does not only advise. It executes.
Alex DiMarco nails the governance gap:
"The governance gap is that infrastructure doesn’t merely inform decisions, it executes them. No one would put a child in charge of life-changing actions without strict boundaries, clear limits, and strong guardrails, yet we often give AI that kind of operational leverage."
So the question becomes:
That is the board-level risk conversation, without the drama.
This is the bit I wish more posts covered. You can move fast and still be responsible. You need a few non-negotiables.
Not a committee. Not “the AI team”. Not “IT”.
Pick one named owner who:
If something goes wrong, you want diagnosis, not blame.
Before prompts, before models, before tool choice, do this:
If you do nothing else, do this.
A simple policy works:
Examples of low-friction checkpoints:
This is the subtle failure mode leaders miss. A system can look fine until it isn’t.
Carlos Rodriguez describes what “grown-up” mitigations look like:
"This story is heartbreaking and as a father of three young adults, I truly hope that OpenAI and others see the importance of crucial mitigations like guardrail degradation monitoring and safety-focused escalation procedures (i.e., detection + action). The limitations of these models are known, but the implications of their failure modes are playing out in real time and we should all pay attention."
In plain terms, you want signals that tell you the system is drifting:
Most escalation paths fail because they are too slow, too formal, or too unclear.
Make it simple:
This protects your customers and your team’s mental load. This stuff is genuinely hard when you’re also trying to hit targets.
If you want a fast, leadership-friendly starting point, run a 60-minute session with Ops, IT, and Risk.
Bring one workflow you want to automate, then answer:
Then pilot it small:
Evidence beats opinion. Iterate.
The OpenClaw story is not a reason to freeze. It’s a reminder that leadership is not about avoiding mistakes. It’s about building systems that fail safely, learn quickly, and protect people.
Agentic workflows are likely to become a normal part of work. The organisations that win will not be the ones with the most automation. They will be the ones with the clearest ownership and the best guardrails.