{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreifgq6zzblqnr3hx3pool7363oaajzxnjo374lv35x65vzetsigkei",
    "uri": "at://did:plc:prhsvfaavfni3y4kgahcdwte/app.bsky.feed.post/3mej45e4swhx2"
  },
  "coverImage": {
    "$type": "blob",
    "ref": {
      "$link": "bafkreibkchppoekkfujhugee5m5opmutfxxkuy2tzr5pd5fv4qolhhrjpa"
    },
    "mimeType": "image/png",
    "size": 623491
  },
  "description": "Your sales team wants AI tools. Leadership wants AI ROI. But your pilots keep stalling because the data foundation isn't there.",
  "path": "/stop-building-ai-pilots-that-go-nowhere/",
  "publishedAt": "2026-02-10T13:49:27.000Z",
  "site": "https://www.revenueoperationsalliance.com",
  "tags": [
    "OnDemand"
  ],
  "textContent": "Your sales team wants AI tools. Leadership wants AI ROI. But your pilots keep stalling because the data foundation isn't there.\n\nYou'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.\n\nIn 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.\n\nOnDemand\n\n### Key takeaways:\n\n  * Why bad data compounds in AI and how to fix it first.\n  * Centralized governance + federated experimentation that prevents chaos.\n  * Deploy narrow AI use cases instead of one giant system.\n  * Build semantic layers so AI understands business context, not just data.\n  * Why 6-12 months of infrastructure work pays off (and how to sell it).\n\n\n\n### What you’ll learn:\n\n**Garbage in, landfill out**\nBad data in AI doesn't just create bad outputs - it compounds exponentially across automated workflows. Fix your data foundation first before scaling AI initiatives.\n\n**Use a two-prong approach**\nCentralized data governance paired with federated experimentation. Empower teams to build use-case-specific solutions while maintaining shared standards, oversight, and trust.\n\n**Why smaller, agentic AI wins**\nInstead of betting on one massive AI system, start with narrow, well-governed, agentic use cases.\n\n**Why AI needs more context than dashboards**\nAI can’t infer meaning the way humans do. Business context must live inside the data itself, not just in reports or dashboards.\n\n### Meet the experts:\n\n\n**Adam Smith, VP Product Data & Analytics, ZoomInfo**\n\nAdam 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.\n\n**Mason McMullin, VP Revenue Operations & Strategy, Alysio**\n\nMason 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.",
  "title": "Stop building AI pilots that go nowhere",
  "updatedAt": "2026-04-02T06:05:47.839Z"
}