<p>In this episode, host Michael Marchuk speaks with Tim Shea, founder and CEO of Latticework Insights, about what it takes to build an enterprise-grade agentic AI program that delivers measurable value. Shea explains that while LLMs are powerful, hallucinations, non-determinism, and high-stakes risk make many agentic initiatives fail without human checks, clear leadership, and strong operating models. He outlines how to decide when a use case truly needs agentic AI versus deterministic automation, using an analytics workflow (extraction, modeling, interpretation, evaluation) to show where agents help most. Shea shares a restaurant-chain example where an agent rapidly replicated unit tests across pipelines to improve data quality and executive confidence. He warns against rushing, token-burning for its own sake, and losing focus on business outcomes, emphasizing upskilling and domain expertise as key differentiators over the next 12–18 months.</p><p><br></p><p>What we talked to Tim about:</p><p>-What Agentic AI Means</p><p>-Why AI Fails in Production</p><p>-When You Need Agents</p><p>-Agent Roles in Analytics</p><p>-Managing Agent Swarms</p><p>-Org Design and Upskilling</p><p>-Measuring Real Outcomes</p><p>-Common Adoption Mistakes</p><p>-Workflow Shifts and Tools</p><p>-High Stakes Industries Limits</p><p><br></p><p>Visit us on our socials:</p><p>🦾 Get started with SS&amp;C Blue Prism: https://okt.to/JcMLdU</p><p>🧑‍💻LinkedIn: https://okt.to/k8zIdp</p><p>✖️Twitter: https://okt.to/fHyd9G</p><p>🙋‍♀️Facebook: https://okt.to/Vyjfiz</p><p>📸Instagram: https://okt.to/5nYvIf</p><p>💭Blog: https://okt.to/QuGqVP</p><p>🤩Case studies: https://okt.to/ft1AMX</p><p><br></p><p>To ensure that you never miss an episode of Transform NOW, be sure to subscribe!</p>