Most standards land with a thud. This one matters.
ISO/IEC 42001 is the first international spec that tries to wrangle AI management into something repeatable. It’s not a checklist. It’s a signal. That AI isn’t a lab project anymore. It’s infrastructure. And it needs to be managed like it.
But here’s the catch, it’s not about compliance. Not yet. It’s about trust.
Trust with buyers who ask, “What happens when your model gets it wrong?”
Trust with regulators who don’t care about your roadmap, just your audit trail.
Trust with your own team when they wonder if the algorithm is smarter than the process.
If you’re building or deploying AI and think this doesn’t apply yet, it does. If you’re selling AI and think this will slow you down, it won’t.
It’ll help you get through procurement without six extra Zooms.
The good news? You don’t need to implement the whole thing. You need to understand where the traps are, and how to show you’re thinking ahead.
Start here:
– Can you trace your model’s decisions back to the data source?
– Do you know who approved that model for production, and when?
– What happens when someone says, “This prediction harmed me. Show your work.”
– Can you rotate out a vendor or API and still keep your risk model intact?
– What’s your AI incident response plan? (No, “retrain it” isn’t a plan.)
42001 doesn’t solve these for you. It tells you which ones you can’t ignore anymore.
You’re not getting a gold star for adopting it. But you might get a faster close with enterprise buyers. Fewer review cycles with legal. And less fear when something breaks in the model.
If you’re serious about AI as a product, not just a feature, this is part of the job now.
Not all of it. But enough that you should at least read the table of contents.
Start with these:
– ISO/IEC 42001 summary from ISO
– Practical take on 42001 by A-LIGN
You don’t need to be certified. You do need to be credible. Start there.
Leave a Reply