Marketing teams love to sell AI legal automation like it is as simple as running an Excel macro, but in regulated environments, replacing human judgment with an unmonitored model is a liability multiplier.

In Part 2 of this three-part conversation, John Turns sits down with Devansh, co-founder of Irys, to tackle the critical balance of reasoning, accuracy, and trust in enterprise AI.

Devansh breaks down the difference between surface-level task automation and true reasoning infrastructure, how to build explainable systems for legal and regulated industries, and where organizations must draw the line between autonomous execution and human-in-the-loop oversight. 

Plus, they confront the ultimate question: when an AI system makes a mistake in a high-stakes workflow, who is actually held accountable?

-----------------------------------------------------------------------------

Case Studies/Links - 

Agentic AI in the Enterprise: Does It Actually Work in the Real World?

https://seisan.com/agentic-ai-enterprise-real-world/

Irys - Legal Work Starts Here.

https://www.irys.ai/

Delta Shield - AI Innovation Without the Risk:
https://seisan.com/delta-shield/

-----------------------------------------------------------------------------

Time Stamps:

0:00 - Introduction

0:52 - Question 1

3:48 - Question 2

9:24 - Question 3

13:26 - Question 4

18:04 - Conclusion