Discover how artificial intelligence is transforming database administration. Learn how SQL Server’s AI-powered features, including Automatic Tuning, Query Store, and Intelligent Query Processing, help detect performance issues, optimize workloads, and prevent resource bottlenecks. Explore real-world examples and live demonstrations to see how AI enables DBAs to work smarter and manage databases proactively.

1. AI Meets
DBA
Transforming Database Administration
with Intelligence
Dhivyadharashini M​
​
​

2. Agenda
 Overview of Webinar
 Understanding Query Store
 Intelligent Query Processing (IQP)
 Automatic Plan Correction (Auto
Tuning)
 AI in SQL Server
 Real-time Demo
 SQL Server 2025 – What’s New?
 Accessing Copilot in SSMS 2025
 Pros & Cons of AI-driven Optimization
 Wrap-up & Q&A

3. Webinar Overview
• SQL Server is
evolving with AI-
driven automation.
• Focus on how Query
Store, IQP, and Auto
Tuning make SQL
Server intelligent.
• Learn to visualize
performance
improvements.
• Explore SQL Server
2025 AI integrations
with Copilot and
Vector Search.

4. What is Query Store?
• Query Store acts as a flight recorder for your
queries.
• Captures query text, plans, runtime stats,
and performance history.
• Helps analyze regressions and compare
plans.
• Enables features like IQP and Auto Tuning.

5. Query Store Data Collection

6. Query Store Key Metrics
• Top Resource Consuming Queries
• Queries with Forced Plans
• Regressed Queries
• Queries with High Variations
• Overall Resource Consumption
• Query Wait Statistics
• Tracked Queries

7. Intelligent Query Processing (IQP)
• Enhances query performance automatically without code changes.
• Uses adaptive algorithms for better execution plans.
• Key features:
- Adaptive Joins
- Batch Mode on Rowstore
- Scalar UDF Inlining
- Table Variable Deferred Compilation

8. Automatic Plan Correction (Auto
Tuning)
• Detects and fixes query regressions automatically.
• Monitors plans and performance over time.
• If a query performs worse, SQL Server reverts to the
previous good plan.
• Keeps databases self-optimizing.

9. Real-time Demo Overview
1. Create
Database and
Tables.
1
2. Insert large
sample data.
2
3. Execute
baseline query
(Plan A).
3
4. Simulate bad
plan (remove
index).
4
5. Observe
regression and
plan change.
5
6. Enable Auto
Tuning to revert
to best plan
automatically.
6

10. Where AI Fits In
• AI = Adaptive Learning
+ Automation.
• SQL Server uses ML
models to detect
regressions.
• Auto-tunes
performance using
Query Store intelligence.
• SQL Copilot assists in
query optimization.
• Vector Search enables
AI data processing in SQL
Server 2025.

11. SQL Server 2025 AI Features
• Vector Search – store and query embeddings directly in SQL.
• AI Copilot in SSMS – assists in query writing and tuning.
• Integration with Azure OpenAI models.
• Enhanced Intelligent Query Processing v4.
• Automatic index and statistics maintenance.
• Real-time AI-driven performance diagnostics.

12. Accessing Copilot in SSMS 2025
• Open SSMS 2025.
• Navigate to “AI Assistance” tab.
• Use Copilot to:
- Write complex SQL queries using natural language.
- Analyze and optimize queries.
- Get AI recommendations for indexing and tuning.
• Example: “Suggest an index for slow-running sales query.”

13. Pros & Cons of AI Optimization
Pros:
• Improves performance
automatically.
• Reduces manual intervention.
• Detects regressions early.
• Learns query behavior.
Cons:
• May force plans incorrectly.
• Query Store adds slight
overhead.
• Depends on accurate statistics.
• Limited AI transparency.

14. Wrap-up & Key Takeaways
• Query Store =
Brain of
Performance
Tuning.
• IQP = Smart
Query Execution.
• Auto Tuning =
Self-Healing
Engine.
• SQL Server 2025
brings AI inside the
engine.
• Copilot = Your AI
DBA Partner.
• Future:
Autonomous SQL
Server with Human
Oversight.

15. Thank You for Attending!