AI in Fabric - Copilot, AI Functions & Data Agents

🎯 The Problem: Your boss says “just add AI to our reports.” Your users want to “ask questions in natural language.” But you’re not a data scientist, and ChatGPT doesn’t know your data. Where do you even start?

💡 This Evening: We’ll show you the AI spectrum in Fabric - from traditional ML to conversational analytics - and which approach fits which use case. No PhD required.

⏱️ Save yourself: The frustration of picking the wrong AI tool. Copilot, AI Functions, and Data Agents solve very different problems.

What you’ll learn

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• 🤖 ML Models – Train and deploy models in Fabric, and WHY MLflow is the backbone of Fabric ML
• 🧪 Experiments – Track runs, compare models, version artifacts, and WHY experiment tracking prevents ML chaos
• ✨ Copilot in Fabric – AI-assisted development across all workloads, and WHY Copilot context matters for quality
• 🧠 AI Functions – Call LLMs from T-SQL and Spark, and WHY AI Functions democratize GenAI for SQL developers
• 💬 Data Agents – Conversational analytics with natural language, and WHY agents beat chatbots for data Q&A

AI Spectrum

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Traditional ML (Train models) → Experiments (Track) → AI Functions (Call LLMs) → Data Agents (Conversational)

Agenda

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Who should attend

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Data Scientists exploring Fabric, Analysts curious about AI capabilities, Developers building AI-powered apps.

Part of the monthly Fabric Meetup Series by The Trusted Advisor.