Originally published on LinkedIn.
You can't build an AI-native product with a team that isn't AI-native.
Most teams still think about AI the wrong way. They start with a human process and ask: "How can AI help people do this faster?" That's the wrong question.
An AI-native team starts with the outcome and asks: "How do we get the AI to achieve this outcome?" Then they work backwards from there. Maybe the AI needs verification. Maybe it needs an approval threshold. Maybe it needs an audit trail. Maybe there are edge cases that still require human judgment.
The software becomes scaffolding around the AI, not the other way around.
This is a hard mindset shift because for most of business history, outcomes were constrained by people. If you wanted more contract reviews, more supplier research, more invoice matching, or more policy enforcement, you hired more people. The software was there to support the human.
Now, for a growing set of tasks, you can spend tokens instead. That doesn't mean humans disappear. It doesn't mean AI can do everything. But it does mean we should stop assuming humans are the default actor in every business process.
Procurement is full of work that AI can already do as well as, and often better than, people: three-way invoice matching, sending NDAs, supplier research, tracking RFP responses, policy enforcement.
The opportunity isn't to help humans do those tasks faster. The opportunity is to have AI do them, then add the controls, verification, and auditability required to trust the result.
The most important mindset shift in AI is moving from: "How do we use AI in this process?" to "Why does a human need to do this at all?"