AI Mythbusters: What Revenue Teams Get Wrong About Putting AI to Work
About this event
<p>Revenue teams are under pressure to put AI to work.</p><p>So naturally, we’ve accumulated a few rules along the way:</p><p><strong>Clean your data before you start. Give sellers better recommendations. Build agents for everything.</strong></p><p></p><p>But how much of that advice actually holds up in practice? 🤔</p><p></p><p>In this live <strong>AI Mythbusters</strong> panel, RevOps leaders who are actively navigating AI inside their organizations will challenge some of the most common assumptions about putting AI to work across revenue teams.</p><p></p><p><strong>Kevin Heraly (VP of Revenue Operations at Demand Science)</strong> and <strong>Sandy Robinson (Quavo Fraud & Disputes) </strong>join <strong>Camela Thompson (Head of Marketing at RevOps Co-op)</strong> and <strong>Sara Kinsey (VP or Marketing & Revenue at Von)</strong> for an operator-led conversation about what they've learned from actually implementing, testing, and governing AI, not just talking about it.</p><p></p><p>We’ll dig into three big myths:</p><p></p><p><strong>Myth #1: “Our data isn’t clean enough for AI.”</strong></p><p>Do you really need a pristine CRM before you start? We’ll explore where imperfect data is manageable, where missing context still creates real risk, and what “AI-ready enough” actually looks like.</p><p></p><p><strong>Myth #2: “If we tell sellers what to do, they’ll do it.”</strong></p><p>A technically correct recommendation is useless if nobody trusts it. We’ll unpack why AI adoption is as much an operational and change-management problem as a technical one—and what actually gets users to act.</p><p></p><p><strong>Myth #3: “We need an agent for everything.”</strong></p><p>More agents don’t automatically mean more value. We’ll talk about what happens when every team starts building its own agents, who owns them after launch, and when a use case would be better served by an automation, process change, or something much simpler.</p><p></p><p>We’ll also tackle <strong>build vs. buy</strong>: what RevOps teams can realistically build themselves, what gets harder once a prototype reaches production, and how to weigh speed, maintenance, risk, and ownership before committing either way.</p><p></p><p>🔑 <strong>Key Takeaways</strong></p><ul><li><p>What actually needs to be true about your <strong>data and context</strong> before you put AI to work</p></li></ul><ul><li><p>Why <strong>trust, workflow fit, and seller agency</strong> matter as much as the quality of an AI recommendation</p></li><li><p>How to avoid an <strong>“agent graveyard”</strong> of disconnected tools, definitions, and owners</p></li><li><p>How to decide when to <strong>build, buy, or simplify</strong></p></li><li><p>What separates an impressive AI prototype from a <strong>production workflow people actually use</strong></p><p></p></li></ul><p>📣 <strong>Speakers</strong></p><ul><li><p><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/matthewvolm/" title="https://www.linkedin.com/in/matthewvolm/">Matt Volm</a>, CEO and Founder at RevOps Co-op</p></li></ul><ul><li><p><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/kevinheraly/" title="https://www.linkedin.com/in/kevinheraly/">Kevin Heraly</a>, VP of GTM Revenue Operations at Demand Science</p></li><li><p><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/sandyrobinson/" title="https://www.linkedin.com/in/sandyrobinson/">Sandy Robinson</a>, VP of Revenue Operations & GTM Enablement at Quavo</p></li><li><p><a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/in/kinseysara/" title="https://www.linkedin.com/in/kinseysara/">Sara Kinsey</a>, VP of Marketing & Revenue at Von</p></li></ul><p></p><p></p><p>Not a member of the RevOps Co-op yet? <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.revopscoop.com/membership/join-the-club" title="https://www.revopscoop.com/membership/join-the-club">Join here</a> to connect with 20,000+ pros who love revenue operations!</p>