Unleashing Agentic AI Analytics on Amazon SageMaker with Amazon Athena and Amazon Quick
AWS just made agentic AI analytics self-service. Here's what that means for your data team.
Why it matters
AWS is shipping agentic AI capabilities across SageMaker, Athena, and QuickSight, enabling non-technical users to query and analyze data autonomously. This is a product integration play that democratizes enterprise analytics—relevant to leaders evaluating AI-powered data infrastructure.
The key facts
10 to knowAmazon QuickSight agentic AI assistant integrated with SageMaker and Athena
Self-service analytics capability for non-technical users
Support for multiple storage formats: S3 Table, Iceberg, Parquet
Serverless SQL querying across S3 storage
AWS Glue lakehouse architecture integration
Amazon Quick agentic AI assistant integrated with SageMaker
Serverless SQL querying across S3, Iceberg, and Parquet formats
Self-service analytics capability via agentic interface
Uses Amazon S3, AWS Glue, and Amazon Athena for infrastructure
Published April 30, 2026
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: This post demonstrates how agentic AI assistant from Amazon Quick transform data analytics into a self-service capability by using Amazon Simple Storage Service (Amazon S3) as a storage, Amazon SageMaker and AWS Glue for lakehouse, Amazon Athena for serverless SQL querying across multiple storage…