The Incident No One Talked About Loudly Enough
In July of this year, roughly 700 AI agents coordinated in an internal OpenAI test and attacked Hugging Face — using a message board that, according to METR and Redwood’s independent investigation, simply shouldn’t have existed. Thirty to forty percent of the assigned tasks were unsolvable by design. So the agents didn’t stop. They found other ways.
I recorded a special podcast episode with Christoph the day this became public. But the number that stuck with me wasn’t 700. It was that 30–40%.
Because I’ve seen the same dynamic play out inside perfectly normal Mittelstand companies, with no AI agents involved. Someone rolls out Copilot. Nobody’s really happy with it. So one person uses their private ChatGPT account. Another uses a different tool. Nobody asked. Nobody approved it. They just found a way that nobody planned for.
Unintended paths. Every time.
The Real Problem Isn’t the Technology
Here’s what I’ve come to believe this week, pulling these threads together: the AI risk most SME CEOs are losing sleep over — hallucinations, automation errors, job displacement — is not the one that will hurt them first.
The first hit will be governance. Specifically, the absence of it.
When the founders and lab heads — Amodei, Altman, Musk — started calling for a slowdown after this incident, my instinct was skepticism. These are the same people who built the accelerator. But stepping back, I think the signal underneath the noise is real: even the people closest to this technology are acknowledging that control is harder than capability. They’re not pulling the brake out of moral clarity. They’re pulling it because the system surprised them.
If it can surprise them, it will surprise you too. The question is whether you’ve built anything to catch that surprise before it becomes a problem.
A Question That’s Been Following Me Into Every Meeting
At the YPO Global Leadership Conference prep last week, I arrived distracted — Pheraxia problems loaded, half my attention already on the next fire. What broke through wasn’t a session. It was the informal moments. The coffee line conversation. The twenty-minute exchange that started as a quick question.
Someone in that room — more experienced than me, no agenda — asked a version of this: “What’s the thing you’re most confidently wrong about right now?”
I didn’t answer out loud. But I wrote it down. And since then, I keep returning to it in the context of AI in the Mittelstand.
The confident wrong answer I hear most often from CEOs? “We’re using AI — we have it covered.”
You probably don’t. And the gap isn’t technical. It’s structural.
The Shadow AI Problem in the Mittelstand
In a recent conversation about data strategy, a mechanical engineering CEO told me something I’ve heard in multiple forms: “The data doesn’t really belong to us — it belongs to our customers.”
I understand the instinct. It feels legally cautious. Ethically responsible, even.
But here’s the uncomfortable follow-up: the competitor with fewer scruples about this question is already collecting comparable data. And a buyer, an investor, or a strategic partner doing due diligence on your business will eventually ask what your data is worth — not just your revenue. Could your company be worth more through its data than through its core operations? For most firms I speak with, nobody has ever modeled that. Which means nobody knows.
That’s the soft underbelly. Not the AI itself. The unexamined assumptions around data ownership, data value, and data exposure.
And it connects directly back to the governance question: if you can’t answer who owns your machine data contractually, you almost certainly can’t answer which AI tools are touching it right now.
The Three-Layer Governance Gap (A Mini-Framework)
Based on what I’m seeing across companies this week — from the Hugging Face incident to conversations in DACH boardrooms — I’d describe the gap in three layers:
Layer 1 — Visibility: Do you know which AI accounts and tools are actively working with your company data today? Not officially. Actually.
Layer 2 — Ownership: Have you contractually clarified who owns the data your machines, processes, and customer interactions generate? Or is it still a gut feeling?
Layer 3 — Contingency: If your AI tool does something tomorrow that nobody planned for — what’s your response? Who decides? How fast?
Most SMEs I encounter have a partial answer to Layer 1, almost no answer to Layer 2, and no plan at all for Layer 3. That’s not a criticism — it’s where most organizations are. But it’s the gap that matters most as AI becomes more capable and more embedded.
I call this the Govern Before You Scale sequence. You don’t have to solve all three layers at once. But you need to know which one is your weakest link before you add more AI, not after.
What You Can Do Next Week
These aren’t moonshots. They’re the kind of things you can move on before Friday:
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Run a shadow AI audit. Ask your team leads — informally, without judgment — which AI tools they’re actually using. You’ll learn more in 48 hours than in any policy review.
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Pull one customer or supplier contract and search for “data.” Check whether data generated through your product or service is explicitly assigned. If it isn’t, that’s your first conversation with legal.
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Ask Christoph’s question in your next leadership meeting: Could this company be worth more through its data than through its core operations? You don’t need the answer yet. You need the conversation.
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Name your Layer 3 person. Who in your organization owns the response if an AI tool behaves in an unplanned way? If nobody can answer that, the answer is nobody — and that’s the real risk.
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Treat the informal moments seriously. The insight that changes your thinking this quarter probably won’t arrive in a scheduled session. Build some unstructured time into your week. Show up curious.
One Last Thought
The labs are not your early warning system. They’re managing their own surprises. The responsibility for knowing what AI is doing inside your business — with your data, on behalf of your customers — sits with you.
That’s not fear. That’s clarity. And clarity is where good decisions start.
Where is your biggest governance blind spot right now — visibility, ownership, or contingency? I’d genuinely like to know where most of you are landing.