Dallas Dutch Girl

Closing the Gap Between Innovation and Trust

SPEAKER: Tim Sanders, Chief Innovation Officer at G2 (he’s in Dallas, great speaker)

Core Idea: AI isn’t limited by capability—it’s limited by trust. Adoption slows because organizations lack confidence, guardrails, and governance.

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Where AI Works Today

• Content optimization
• Campaign automation
• Audience research (incl. synthetic audiences > ICPs)

AI is already a force multiplier, not just a productivity tool.

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The Trust Gap

Teams still over-rely on human approval due to:

• Fear of errors
• Missing guardrails
• Low institutional trust

The problem isn’t performance—it’s trust in performance.

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AI vs. Humans

• AI errors are declining and self-correct quickly
• Humans are often inconsistent and slower to correct
• AI hallucinations are less (humans do it even more)
• Claude’s hallucinations are very high (don’t use for research); Chat GPT 5.5 is best for this

Humans shift from doing → deciding and executing → verifying

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AI = Capacity Multiplier

• 300×–10,000× potential output scale
• Not a cost-cutting tool → a growth engine
• Supports “Collaborative Intelligence” (humans + AI)

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From Tools to Teammates

Big mistake: treating AI as a tool (instead, treat it like a teammate)

Better: assign levels of autonomy

• Low: drafting
• Mid: optimization
• High: modeling & decision support

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How to Build Trust

1. Combine AI Types

• Background: optimization, strategic research, insights
• Foreground: automation, personalization, generation

2. Verification Systems

• Use trusted internal data
• Constrain AI to approved sources

3. Guardrails > Fear

• Define rules and boundaries to enable safe autonomy

Build a repository for what good looks like > have AI only reference that

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Operating Shift

• AI works continuously; humans don’t
• Marketers become pilots, not passengers

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Key Takeaways

• Trust—not capability—is the barrier
• AI elevates human judgment
• Treat agents as teammates
• Verified knowledge bases/systems unlock scale

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Actions

• Build a trusted internal knowledge base for AI to reference
• Define agent autonomy levels (low, mid, high)
• Design workflows: AI = speed, humans = validation
• Start small and scale trust over time

Book Tim recommended: Co-Intelligence: Living & Working with AI

*This content was developed with the assistance of AI tools.