Episode
Stop Building Chatbots: How to Codify Your Logic into a Digital Twin
- Published
- Jun 2, 2026
- Duration seconds
- 4055
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Summary
Most organizations are building chatbots because they're easy to deploy, easy to demonstrate, and relatively inexpensive to operate. But while chatbots can answer questions, they rarely transform how work gets done. The organizations creating the biggest impact with AI are focusing on something entirely different: codifying expertise into digital twins that can reason, diagnose, and guide decision-making.In this episode of M365 FM, Mirko Peters explores why the future of enterprise AI isn't about better conversations—it's about better logic. You'll learn why most organizations are optimizing the wrong layer of the technology stack and how digital twins can capture expert knowledge, automate decision frameworks, and drive measurable business outcomes. WHAT'S THE DIFFERENCE? A chatbot answers questions. A digital twin helps make decisions.While both technologies may use the same underlying AI models, they solve fundamentally different problems. Chatbots focus on information retrieval and conversational experiences. Digital twins focus on workflows, diagnostics, business processes, governance, and operational outcomes.In this episode, you'll discover: Why most AI projects fail to move beyond pilot programs The difference between conversational AI and decision intelligence How organizations can codify expert knowledge into reusable logic Why workflow understanding matters more than prompt engineering BUILDING AI THAT THINKS Most expertise inside an organization exists as tribal knowledge. The best employees know how to diagnose problems, evaluate risks, identify patterns, and make decisions—but that logic rarely exists in documentation.Learn how to transform expert reasoning into structured decision frameworks using Microsoft Copilot Studio, Dataverse, Microsoft Graph, Log…