Dynamic Decisions Podcast

Dr. Lorien Pratt didn't just watch the AI revolution happen, she helped build it. In the early 1990s, as a computer science professor, she invented transfer learning, the technique now running underneath every large language model and computer vision system in use today. Then she walked away from pure machine learning to found an entirely new discipline: decision intelligence.

In this episode, Lorien joins host Teasha Cable, her mentee, friend, and co-founder at OpenDI, for a conversation that skips past the AI hype and gets into what actually changes how organizations decide.

They dig into the last mile problem: why a trillion dollar resources company spent ten years and tens of millions of dollars building a digital twin that nobody ever deployed. Lorien explains why KPI dashboards function like a GPS that only says "there's traffic" instead of telling you where to turn, and why that gap between information and action is where most AI investment quietly disappears.

They also tackle the question everyone is asking in 2026: where does agentic AI actually belong? Lorien draws a sharp line between decisions that happen inside the digital world, where agents shine, and decisions with real world consequences, like hiring, contracts, and opening a new business, where she argues large language models remain fundamentally unreliable.

Along the way, Lorien walks through a real example of organizational silos derailing a government agency's building decisions, explains the authority and responsibility mismatch that drives leaders crazy, and takes Teasha's decision-making persona quiz live on air, with results that might surprise you.

If your organization has all the data and analytics money can buy but still can't seem to make a clear decision, this conversation names the problem and shows you the way through it. Listen now, and see where you'd land on the same persona test.