In the final part of this three-part conversation, Mark Kavanagh and I close things out with where AI actually fits into RTM today ... and where it might be headed.

Mark walks through how he actually uses tools like Claude in his day-to-day: not to make decisions, but as a way to surface and present data so the real thinking still happens between people. We get into how far he trusts it, whether there's a point where AI starts overriding human judgment rather than just informing it, and what RTM might look like in five years if the industry's AI predictions hold up. Along the way, Mark pushes back on some of the hype, including his skepticism about how much of the current AI push is genuinely value-driven versus share-price-driven, before we wrap with why, twenty years in, he's still not bored of RTM.

That's the full three-part conversation ... thanks for listening.

In part two of this three-part conversation, Mark Kavanagh and I get into what happens when the plan meets reality mid-week, and the two competing philosophies on what to do about it.

Philosophy A: the plan is the plan, RTM reacts and mitigates, and any gaps get folded into next week's forecast. Philosophy B: adjust in real time as the variance shows up. We dig into why Mark comes down firmly on one side, what gets lost when you "move the goalposts" mid-cycle, and why nobody ever quite says "the forecast was wrong." From there we get into the politics of blame between RTM and forecasting, the "big picture" deflection tactic used to wave away real problems, and finally.... should RTM have a seat at the table when the plan is actually being built?

Part 3 : where AI actually fits into RTM decision-making ... is coming soon.

In part one of a three-part conversation, Mark Kavanagh joins to dig into what "good" Real-Time Management actually looks like, and why that's a harder question than it sounds.