AI Meets DBA: Transforming Database Administration with Intelligence

DBAs have spent years reacting. A query slows down, an alert fires, someone digs through execution plans at 11 PM trying to figure out what changed. SQL Server's AI-powered features are starting to shift that pattern, and this session is about what that shift actually looks like in practice.

Dhivya M walks through Automatic Tuning, Query Store, and Intelligent Query Processing, not as feature-list bullet points but as tools that catch problems before they become incidents. Live demonstrations show what AI-assisted detection and optimisation look like against real workloads, not sanitised examples.

The bigger point isn't that AI replaces a DBA's judgment. It's that it removes a lot of the guesswork that used to eat up a DBA's time.

• How Automatic Tuning catches regressions without manual intervention
• What Query Store actually surfaces that manual monitoring tends to miss
• How Intelligent Query Processing prevents bottlenecks before they hit production
• Where AI genuinely changes DBA workflows versus where it's still just automation with a new name

Most performance issues get caught late because nobody was watching closely enough. AI changes what "watching closely" means.

• How SQL Server's AI-powered features detect and resolve performance issues automatically
• What Query Store reveals about workload behaviour that manual review often misses
• How Intelligent Query Processing prevents resource bottlenecks before they escalate
• Real-world examples of DBAs managing databases proactively instead of reactively

AI doesn't take DBAs out of the loop. It moves them from firefighting to prevention, and that's a meaningfully different job.