Stop Worrying, Start Wiring: Azure Serverless for the AI Era

AI is no longer just a buzzword — it’s a fundamental part of modern software. But for developers, the challenge isn’t what AI can do — it’s how to integrate it into scalable, cost-efficient, and maintainable applications. That’s where Azure Serverless comes in.

In this session, we’ll ...

AI is no longer just a buzzword — it’s a fundamental part of modern software. But for developers, the challenge isn’t what AI can do — it’s how to integrate it into scalable, cost-efficient, and maintainable applications. That’s where Azure Serverless comes in.

In this session, we’ll bridge the gap between AI and application engineering. You’ll discover how Azure Functions, Event Grid, and Container Apps can serve as the event-driven backbone of intelligent systems. We’ll explore real-world patterns like automated inference pipelines, orchestrating multi-step AI workflows, and using serverless triggers to activate model predictions or data processing jobs.

To bring it all together, we’ll build and run a live demo: the AI Insights Pipeline — a simple but powerful example where uploading a text file to Blob Storage triggers an Azure Function, calls Azure OpenAI to generate a summary, and sends the result to Microsoft Teams via Logic Apps.

By the end, you’ll understand how to confidently build and deploy intelligent, event-driven solutions with Azure Serverless — without managing infrastructure, worrying about scale, or breaking your budget.

You’ll stop worrying about AI — and start wiring it into everything you build.

🎯 Learning Outcomes

After attending this session, participants will be able to:

Identify when and how to use Azure Serverless components (Functions, Logic Apps, Event Grid, Container Apps) for AI-driven workflows.

Build event-driven AI pipelines that react to real-world triggers (file uploads, API calls, or messages).

Integrate Azure OpenAI, Cognitive Services, or custom ML models seamlessly using serverless triggers.

Apply best practices for scaling, cost optimization, and observability for AI workloads.

Design maintainable and secure AI-powered serverless applications.