Everyone asks when the big AI labs will decide safety matters more than capability. It's the wrong question. The right question is: what incentives would get them to change?
Incentive Reality
Labs are businesses. Their customers reward capability. They'll ship the most powerful models that reach the largest market while keeping the failure rate within what customers tolerate. That's a feature of markets, not a bug.
That means we shouldn't look to builders as the primary saviors. They're optimizing for adoption and capability. They'll improve safety when there's economic pressure. And historically, that pressure comes after incidents.
Look at SOC2. It didn't appear because vendors decided to be more secure. It appeared because customers demanded proof after repeated security and privacy incidents. Standards arise from buyer pressure and incident-driven regulation. AI will follow the same arc.
Cold War Dynamics
There's another structural constraint: geopolitics. Why would an American lab slow down if a Chinese lab won't? You won't get unilateral restraint in a competitive global market. That's classic Cold War-like behavior: neither side wants to yield first.
Practical Framework for Buyers
If buyers control the risk, here's what they should do:
- Quantify acceptable failure rates and bake them into procurement.
- Demand audit-ready evidence: logs, Trust Scores, supervised behavior metrics.
- Insist on containment: air gaps, segmentation, policy enforcement in code.
- Implement supervision layers that treat AI as a black box and monitor for drift.
This isn't a resignation to doom. It's pragmatic. Recognize who's incentivized to act and where the power lies. If we want safer AI, buyers must act. Push vendors, change procurement, and build the supervision stacks that keep systems in check. That's how we've solved similar problems before.
If you're ready to take control of your AI safety, we can help.
