How are you gonna come back for that one?

I think there's a lot in this area that we can learn from history.

You know, in 1962, the question was, do we trust IBM? Now it's 2026, and the question is, do we trust the model? NASA was about to send John Glenn, and as you know, I'm, I'm a space nerd, so any opportunity to throw something in there, I'll take it.

But one of the first American astronauts into orbit around Earth, the flight path had been calculated by a brand-new IBM computer.

But before Glenn would get in the capsule, he asked to have Katherine Johnson check the numbers by hand.

Uh, Johnson was one of the NASA's...

They called them human computers.

[laughs]

But real question for you, do you think that the physical freight automation, so things like driverless trucks, can actually become autonomous before our supply chain control rooms do? Yeah.

Yeah, before I answer your question, I love this topic.

Just a couple nights ago, I was sitting on the couch with my boys, showing them a TikTok video of an autonomous freight truck.

And it's just incredible.

It's amazing to see how much it's developed.

And whether it's personal vehicles like Zoox or Waymo, or whether it's all the way up to full supply chain driverless trucks over the highways, we live in an incredible time.

I would say in terms of could physical freight go autonomous before our supply chain control rooms do? Absolutely.

If a company is renting its physical network and it's outsourcing its operational data, what actually remains as part of the supply chain organization?

So if operations leaders shouldn't just be looking at headcount or direct spend, what are those metrics that actually prove AI is driving real enterprise value? What should they really be looking at? What should be on their scorecards?

Yeah, Cody, one of the challenges I saw members face as they move from more human activities to more autonomous activities is that their metrics don't always reflect that new operating reality.

You know, for example, when I've led planning teams in the past, the expectation was that the planner was taking the forecast and then using their knowledge and understanding their suppliers and insight to really judge that process.

Whereas modern companies with agentic systems, they're increasingly measuring their planners against not touching the plan.

or adjusting it and really trusting the agentic output.

So we mapped metrics along a continuum from baseline metrics where you ask things like, is the process healthy, to more advanced and transformational metrics, which really reflect if the supply chain is helping the enterprise really as a partner to make better decisions faster.

These transformational metrics, you know, they're measuring things like decision latency, the percentage of low value planner or analyst work that you've been able to automate and the percentage of time your teams are spending on administrative work versus truly value added activities like.

So to me, that just kind of underlines the fact that business leaders really do need to take the long view on AI rather than just obsessing about quarterly results.