Data, trust, and autonomy: An executive conversation on enterprise AI
October 28, 2026
11 AM - 12 PM EDT
Virtual
George Fraser
Andi Gutman
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The bottleneck has moved: Discover why model improvements may no longer be the biggest factor in enterprise AI success — and where leaders should focus next
AI is moving from answers to action: See why enterprise AI is evolving from copilots that assist employees to autonomous agents that execute business tasks — and what leaders must consider before giving them greater control
Why more context can make AI worse: Explore when additional context reduces accuracy and how to give agents the smallest amount of information needed to reach the right answer
Autonomy is a spectrum: Decide which actions agents should take independently, when humans should remain involved, and how to expand autonomy as trust grows
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Fivetran and Google Cloud leaders explore why data — not model capability — is becoming the defining challenge for enterprise AI and what must change as companies move from copilots to autonomous agents.
For the past several years, the AI conversation has centered on models. But as model reasoning improves, the competitive advantage is shifting to something enterprises already have in abundance, yet they struggle to use effectively: their data. As Andi Gutmans, Vice President and General Manager of Google Agentic Data Cloud, puts it, “the data is really the lifeline of AI.”
In this candid executive conversation, Gutmans joins George Fraser, CEO of Fivetran and dbt Labs, for a candid executive conversation about the next phase of enterprise AI. They examine how agent-scale workloads will change data architecture, why giving AI more semantic context can sometimes produce worse results, and how leaders should determine where autonomous action ends and human oversight begins.
Watch the conversation to explore what it takes to connect enterprise data to AI and move from experimentation to trusted, autonomous action.
The bottleneck has moved: Discover why model improvements may no longer be the biggest factor in enterprise AI success — and where leaders should focus next
AI is moving from answers to action: See why enterprise AI is evolving from copilots that assist employees to autonomous agents that execute business tasks — and what leaders must consider before giving them greater control
Why more context can make AI worse: Explore when additional context reduces accuracy and how to give agents the smallest amount of information needed to reach the right answer
Autonomy is a spectrum: Decide which actions agents should take independently, when humans should remain involved, and how to expand autonomy as trust grows
George Fraser
Andi Gutman
George Fraser
Andi Gutman
Fivetran and Google Cloud leaders explore why data — not model capability — is becoming the defining challenge for enterprise AI and what must change as companies move from copilots to autonomous agents.
For the past several years, the AI conversation has centered on models. But as model reasoning improves, the competitive advantage is shifting to something enterprises already have in abundance, yet they struggle to use effectively: their data. As Andi Gutmans, Vice President and General Manager of Google Agentic Data Cloud, puts it, “the data is really the lifeline of AI.”
In this candid executive conversation, Gutmans joins George Fraser, CEO of Fivetran and dbt Labs, for a candid executive conversation about the next phase of enterprise AI. They examine how agent-scale workloads will change data architecture, why giving AI more semantic context can sometimes produce worse results, and how leaders should determine where autonomous action ends and human oversight begins.
Watch the conversation to explore what it takes to connect enterprise data to AI and move from experimentation to trusted, autonomous action.