The Enterprise AI Show

The Enterprise AI Show explores the AI journey for Enterprise companies around the world. [formerly The Cloudcast]

As the AI revolution moves from experimentation to execution, The Enterprise AI Show provides the clarity needed to lead. Join Aaron Delp and Brian Gracely as they explore the intersection of generative AI, enterprise systems, and global business strategy. Each episode features clear-headed conversations with the people making actual decisions—founders, investors, and practitioners—focusing on the technical architectures and business models that drive real-world ROI.

New shows every Wednesday and Sunday.

Topics: Enterprise AI strategy · The AI Economy · LLMs in production · AI leadership · Agentic AI · Digital Sovereignty · Machine Learning · AI startups · Cloud Computing

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The Enterprise AI Show

Can AI Agents be held Accountable?

May 20, 2026 • Massive Studios

0:00 | 30:06

SUMMARY: As AI Agents are being brought into complex, regulated workflows, we explore the importance of accountability and accuracy, and how platforms and harnesses accomplish that goal. Can the CFO really fall in love with AI?

GUEST: Ram Venkatesh, Co-Founder/CTO of Sema4.ai

SHOW: 1029

SHOW TRANSCRIPT: The Enterprise AI Show #1029 Transcript

SHOW VIDEO: https://youtu.be/Lc3XS44Ixg4

SHOW SPONSORS:

Nasuni - Activate your data for AI and request a demo
ShareGate - ShareGate Protect. Microsoft 365 Governance. We got this.

SHOW NOTES:

Topic 1 - Welcome to the show. Tell us about your background, and what led you to create Sema4.ai?.

Topic 2 - AI Agents vs. Automation 2.0. What Actually Changed. Tell us about the Sema4.ai platform and capabilities. What challenges does it solve today?

Topic 3 - You’re initially focused on solving challenges for the CFO, which means there is a ROI-focus all the time. Why did you target that segment of the business first?

Topic 3a - What are the biggest hidden costs in enterprise AI deployments today?

Topic 4 - Sema4.ai emphasizes “your LLM, your VPC, your data.” What are the biggest considerations for companies looking to create these private/sovereign AI solutions? What typically gets overlooked?

Topic 5 - How do you tend to frame the conversation about AI trustworthiness, and the role of humans vs. agents for enterprise work?

Topic 6 - It feels like so much has changed or evolved with AI in the last 2-3 years. How does an Enterprise think about this much change for something that will be core to many critical applications? What will the Enterprise Architecture look like in 2 years?

Topic 7 - Sema4.ai emerged partly from the acquisition of Robocorp and has roots in open-source automation. Do you have a perspective on the role open-source will play in AI going forward?

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