In this episode, Sanjay Sankolli, Chief Architect for AI and Data at Truist, joins Karan Jain, Founder and CEO of NayaOne, to explore why enterprise AI often stalls before delivering real value.

The conversation focuses on the structural challenges behind AI adoption, including weak data foundations, misaligned operating models, and the complexity of scaling in regulated environments.

You’ll hear:

🔹Why AI must be treated as an operating model shift, not just a technology upgrade

🔹What changes when moving from pilot to production

🔹Why the “last mile” is where most AI initiatives break down

🔹How regulatory uncertainty is influencing enterprise decision-making

🔹Why multi-vendor evaluation is becoming the new norm

This is Part 1 of a 4-part series on operationalizing AI in the enterprise.

AI might be the headline, but execution is the story.

In the final part of this three-part series, Philippe Rambach gets practical about what it takes to make AI work inside a large enterprise.

This episode explores:

🔸Why most of AI transformation is really change management

🔸What goes wrong when AI is introduced as a new tool

🔸How embedding AI into existing workflows drives adoption

🔸Why training 140,000 employees is not optional

🔸And how AI leaders spend their time recalibrating expectations

“If you need 100% accuracy, let’s not waste time.”

A grounded conversation on what it takes to move AI from experimentation to real business impact.

Featuring Rambach in conversation with Dr. Julian Schirmer, Co-Founder at OAO.

In this episode, Edgar Gallo, Chief Data Officer at Daimler Truck North America, shares how agentic AI is being applied to real-world supply chain challenges.

The discussion with Susan Wilson of Alation, focuses on how AI agents can reduce repetitive work, support planners, and improve responsiveness in complex manufacturing environments.

Gallo explains how breaking work into decision-making and execution enables AI to handle structured tasks while preserving human judgment where it matters most.

The conversation also explores how trust is built, not through technology alone, but when AI and human reasoning consistently arrive at the same outcomes.

This episode offers a grounded perspective on what it takes to move from AI experimentation to real operational value.