A 30% error rate sounds fine until you realize AI is making calls on your health or money. That's where things get risky. Some projects are tackling this head-on through multi-model verification—essentially cross-checking AI decisions across different systems to catch errors before they happen. The research shows you can get that error rate down dramatically, pushing toward near-zero failures. That changes everything. When AI handles high-stakes decisions, you don't want to gamble. With better verification mechanisms in place, you can actually trust the system to do what it's supposed to do.