As the insurance industry embraces artificial intelligence to streamline operations, data professionals are playing a central role in making it all work. From predictive underwriting to automated claims triage, AI systems depend on robust, well-architected data pipelines that can scale, comply, and deliver insights in real time.

In this session, we explore how global insurers are using enterprise data platforms—including SQL Server, Azure Synapse, and Power BI—to fuel AI-powered workflows that transform underwriting, fraud detection, and customer engagement. With real-world examples, we’ll demonstrate how intelligent data pipelines support automation across high-volume operations, where accuracy, latency, and governance are critical.

You’ll see how data teams enable machine learning, NLP, and robotic process automation by orchestrating secure, high-throughput environments using SSIS, SQL Server ML Services, and Azure Data Factory. These systems power real-time scoring, process thousands of applications per hour, and deliver fraud detection gains over 60%—all while adhering to regulatory frameworks like GDPR and SOC 2.

We’ll also cover how to embed predictive analytics and AI outputs directly into business intelligence layers using SQL-backed APIs and Power BI dashboards, creating a seamless experience from raw data to decision-making.

Attendees will walk away with a blueprint for scaling AI initiatives without reinventing their data stack. Learn how to integrate modern AI into existing Microsoft data ecosystems using familiar tools, and how to optimize data quality, model feedback loops, and observability in production environments.

This session is ideal for DBAs, data engineers, BI developers, and analytics leads looking to bridge the gap between data platforms and intelligent automation—unlocking measurable value and operational agility in enterprise insurance and beyond.