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# Stop building AI pilots that go nowhere
- URL: https://www.revenueoperationsalliance.com/stop-building-ai-pilots-that-go-nowhere/
- Published: 2026-02-10T13:49:27.000Z
- Updated: 2026-04-02T06:05:47.000Z
- Description: Your sales team wants AI tools. Leadership wants AI ROI. But your pilots keep stalling because the data foundation isn't there.
- Author: Revenue Operations Alliance
- Tags: AI & automation, Revenue Growth, Revenue Operations Alliance, Live session

Your sales team wants AI tools. Leadership wants AI ROI. But your pilots keep stalling because the data foundation isn't there.

You're not alone. While **60%** of executives understand AI's strategic impact, fewer than **30%** have the data governance to operationalize it and only **20%** have moved AI pilots to production at scale.

In this free live session with **ZoomInfo**, you'll learn how to break the perpetual pilot cycle and get AI into production without rebuilding your entire tech stack.

[OnDemand](https://pmmalliance.ondemand.goldcast.io/on-demand/fa385b4d-aa3c-4427-8c66-ba85d8f0c471)

### Key takeaways:

- Why bad data compounds in AI and how to fix it first.
- Centralized governance + federated experimentation that prevents chaos.
- Deploy narrow AI use cases instead of one giant system.
- Build semantic layers so AI understands business context, not just data.
- Why 6-12 months of infrastructure work pays off (and how to sell it).

### What you’ll learn:

**Garbage in, landfill out**  
Bad data in AI doesn't just create bad outputs - it compounds exponentially across automated workflows. Fix your data foundation first before scaling AI initiatives.

**Use a two-prong approach**  
Centralized data governance paired with federated experimentation. Empower teams to build use-case-specific solutions while maintaining shared standards, oversight, and trust.

**Why smaller, agentic AI wins**  
Instead of betting on one massive AI system, start with narrow, well-governed, agentic use cases. 

**Why AI needs more context than dashboards**  
AI can’t infer meaning the way humans do. Business context must live inside the data itself, not just in reports or dashboards. 

### Meet the experts:  

**Adam Smith, VP Product Data & Analytics, ZoomInfo**

Adam Smith leads the Intelligence product team focused on applied AI, machine learning, and data science. He focuses on bridging the gap between AI innovation and production-ready solutions, helping organizations move beyond proof-of-concepts to scaled AI implementations. 

![](https://storage.ghost.io/c/62/19/6219f8f5-5d35-43bc-82c3-ce0aeb6b2cc9/content/images/2026/02/Adam_Smith_ZI-1.jpeg)

**Mason McMullin, VP Revenue Operations & Strategy, Alysio**

Mason McMullin drives operational excellence, scales revenue processes, and aligns strategy with execution across **Alysio**. His expertise in data-driven decision-making, process optimization, and analytical modeling helps revenue teams achieve higher performance, predictability, and sustained growth through AI-driven sales strategies.

![](https://storage.ghost.io/c/62/19/6219f8f5-5d35-43bc-82c3-ce0aeb6b2cc9/content/images/2026/02/mason_mcmullin_alysio-1.jpeg)