563: Go Beyond AI: Discover the Outcome Advantage, with FourKites

Matt Elenjickal of FourKites talks about AI: key roadblocks to keeping exec buy-in; focusing on outcomes, metrics & shifting from automation to execution.

IN THIS EPISODE WE DISCUSS: [02.52] The mindset shift needed in AI and new technology, and why the real question isn't "What can AI do?" but "What outcome am I accountable for?"

"In my role, I talk to a lot of supply chain leaders. And every leader is accountable for an outcome, not a capability. So a VP of supply chain isn't measured on whether or not they've adopted AI – they're measured on whether the product is arriving on-time, in-full, and at the right cost."

"Most conversations start with technology and work backwards."

[05.40] The difference between optimizing an individual task and optimizing an end-to-end business outcome, and why an outcomes-first approach is so important as companies invest more heavily in AI.

"Teams are optimizing in siloes, and that doesn't add up to C-Level outcomes."

[11.00] Why applying AI to internal data often hits a ceiling, and the role external data plays in making AI genuinely effective.

"The ceiling is the context. So when you work with your internal data, you're only optimizing what you know. You have no idea what's happening outside… But there are a lot of external factors that are impacting your supply chain."

[14.26] Why the conversation is shifting from AI that automates to AI that actually executes, the difference between the two, and how executives should rethink their AI strategy if they want measurable business outcomes rather than isolated productivity gains.

[16.51] Why, as AI takes on more execution, traditional business metrics don't tell the full story, and why 'invisible success' is a real challenge for leaders.

"When you think about traditional metrics, they count what happened. But when you think about prevention, it's measuring what didn't happen. And it's very hard for a CFO to credit something that didn't happen."

[21.03] The new metrics organizations should be looking at to understand AI's real impact.